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Two problems exist in the study of the trajectory optimization problem of powered hypersonic gliding vehicles (HGVs) due to insufficient consideration of the overall design constraints as well as the strong couplings among relevant disciplines: (1) the engine and thrust models are not compatible with the existing HGV; (2) configuration parameters of the HGV are not included as design variables during trajectory optimization (i.e., propulsion discipline is decoupled in the process of the HGV configuration design), thus failing to fully explore the effect of power to improve the performance of the HGV. Therefore, the application of multidisciplinary design optimization (MDO) in the overall design of powered HGVs should be investigated. First, a MDO task analysis and a multidisciplinary model analysis are carried out for the powered HGV. Second, the multidisciplinary optimization problem is defined, and the couplings between disciplines of the powered HGV are analyzed so that a six-discipline model is established that is suitable for the overall design process, including the parameterized configuration geometry, aerodynamics, propulsion, mass properties, trajectory, and aerodynamic heat/thermal protection system (TPS). Finally, a surrogate model is used to replace the time-consuming accurate model, and numerical optimization examples verify the effectiveness of the method. The optimization results show that the method has a good convergence speed, which increases the gliding range of the optimized vehicle by 8.37%. In addition, by decoupling the propulsion discipline, the validation shows that the coupled propulsion discipline during the overall design can increase the range of the powered HGV by 3.87% compared to the powered HGV optimized with the decoupled propulsion discipline. The work done in this paper provides a new design idea for the overall design of a powered HGV. [ABSTRACT FROM AUTHOR]

In this paper, the reentry phase of the Aerospaceplane is taken as the research object, and the performance parameters of the reusable rocket of a private company are analyzed. Aiming at the guidance and control scheme of the spacecraft returning to the reentry trajectory in the real environment, the original natural algorithm is optimized by considering various reentry flight constraints, and the improved original natural algorithm is used to optimize the reentry trajectory of the Aerospaceplane. We obtained two types of reentry trajectories in the presence of large flight-restricted areas, the "S-type" trajectory and the "spiral-type" trajectory, and obtained data on various influencing factors. The results showed that the basic state parameters of the spiral trajectory optimized using the improved original natural algorithm after adding constraints met the constraint conditions. The aerodynamic heating rate and overload of the spiral reentry trajectory were to some extent greater than those of the S-type trajectory. Under the increasingly stringent requirements of the aerospace environment, new requirements were put forward for the thermal protection system to meet the wider environmental situation. This paper uses the improved original natural algorithm for the first time and applies it to the field of aerospace reentry and entry and adds more constraints to this algorithm for computation. Besides, for the first time, the macroscopic nature of trajectory types is used as a comparative element for parameter comparison, providing a reference basis for selecting trajectory optimization directions from the macroscopic perspective of trajectory types. [ABSTRACT FROM AUTHOR]

Regarding the issue of information freshness in systems that aid in data collection using unmanned aerial vehicles (UAVs), a data collection algorithm that is based on freshness and UAV assistance is proposed. Under the limitations of wireless sensor node communication distance and UAV parameters, the optimization problem of minimizing the average spatial correlation age of information (SCAoI) of all nodes in the area is set up. This problem is solved by optimizing the number of clusters, UAV flight trajectories, and the order of data collection from cluster member nodes. The maximum communication distance of the nodes is used as the cluster formation radius, and the maximum-minimum distance clustering algorithm is used to cluster the nodes in the region to obtain the minimum number of clusters. After it has been proven that the trajectory optimization problem in this study is NP-hard, the ant colony algorithm is applied to obtain the minimum flight time and the corresponding trajectory. By using the greedy algorithm to determine the member nodes in the sequence of data collection for a cluster, the instantaneous SCAoI of the UAV arriving at the cluster head is solved. Simulation results show that the proposed algorithm in this paper can effectively improve the freshness of data and reduce the average SCAoI of the system compared with the algorithm in the comparative literature, reducing the average SCAoI by about 61%. [ABSTRACT FROM AUTHOR]

The development of connected vehicle (CV) technology has created conditions for improving the traffic efficiency of intersections and provided support for more effective speed guidance at signalized intersections. First, this paper proposes a platoon speed guidance strategy to reduce the fuel consumption and delay of the platoon passing through the intersection and smooth traffic oscillation, which includes constant speed guidance, deceleration guidance, acceleration guidance, and stop guidance. Then, the optimal speed calculation method is designed, including the calculation of the platoon's passable period and maximum number of passing vehicles, the platoon restructure method, the analysis of the trajectory of the vehicles, and the calculation of the optimal trajectory of the platoon based on the goal of minimum fuel consumption and delay. Finally, eight different intersection scenarios are designed to simulate the proposed platoon speed guidance strategy. The results show that the platoon speed guidance strategy can effectively reduce the fuel consumption and delay of the platoon passing through the intersection and smooth traffic oscillation. In addition, the influences of queue length and CV penetration rate on the platoon speed guidance strategy are also discussed. The results show that when the queue length affects the passable period, the improvement in fuel consumption, drive time, and delay will decrease as the queue length increases. And as the penetration rate increases, the strategy becomes increasingly effective in reducing the delay and fuel consumption of the platoon in general. [ABSTRACT FROM AUTHOR]

In order to make the new air duct structure trajectory correction projectile have good dynamic correction control effect, the control strategy of the projectile's correction mechanism is studied in this paper. A design method of trajectory correction control strategy based on particle swarm optimization-cuckoo search (PSO-CS) hybrid algorithm is proposed to obtain the optimal control parameters that can make the projectile flight stable and correct accurately. Firstly, the mathematical model of the air duct structure projectile is established. Secondly, the multiobjective optimization problem is analyzed. The projectile's correction control strategy optimization model is established by taking the start control time, the number of corrections, the correction working time, and the interval time as the control variables. The optimization model innovatively considers the influence of the correction action on the flight stability of the projectile and the influence of the start control time on the correction range. Finally, the PSO-CS hybrid algorithm is used to design the calculation method of the optimization model and solve the optimal correction working parameters. The simulation results indicate that the control strategy optimization model can be solved by the proposed calculation method. Moreover, optimal correction working parameters of the correction mechanism in the current state can be obtained. Compared with the results of using single PSO algorithm and CS algorithm, the correction scheme calculated by PSO-CS hybrid optimization algorithm is better. This correction control scheme can effectively reduce the impact point deviation and make the projectile flight stable. At the same time, the circular error probable (CEP) of the projectile after correction is reduced from 42.3 m to 4.6 m while the impact point dispersion is lowered. The research results show that the design method of correction control strategy proposed in this paper is effective for trajectory correction of the new air duct structure projectile. [ABSTRACT FROM AUTHOR]

With increasing energy consumption in urban rail transit systems, researchers have paid significant attention to energy-saving train control. In this paper, we propose an effective train trajectory optimization method to reduce the energy consumption based on coasting control, in which coasting control regimes are added to balance running time and energy consumption. For better determining the starting points of coasting control regimes, the whole train running process is divided into several subintervals. Then, aiming to achieve energy efficiency, coasting regimes are added to the subintervals with high energy-saving effects, in which more energy consumption can be reduced with the same running time addition. Based on this, a coasting control method is proposed to generate energy-saving trajectories considering train dynamics, safety, and punctuality. In addition, the proposed method can solve the multisection energy-saving train trajectory optimization problem to obtain optimal running time schemes and related trajectories. Finally, numerical examples based on one of the Beijing metro lines are implemented to verify the effectiveness of the proposed method. The results show that, for the single-section train control problem, the proposed coasting control algorithm can achieve significant energy-saving effects compared to the practical trajectory and calculate energy-saving trajectory in shorter computation times compared to the dynamic programming method. Meanwhile, for the multisection train control problem, energy consumption can be further reduced by optimizing trajectories and running times integratedly. [ABSTRACT FROM AUTHOR]

During oil and gas exploitation, wellbore stability has always been the focus of many scholars. Instability of wellbore will lead to washouts, breakout, stuck pipe, mud loss, and so on, even the abandon of the well. Shale rock is widely distributed in nature and must be taken into account in some rock engineering applications. In order to evaluate the strength anisotropy and the influence of moisture content of the wellbore integrity, the LMX outcrops are divided into three groups to carry out triaxial strength experiment. Based on the fitting method of collaborative search, the strength parameters of different moisture contents are determined; then, the effect of strength anisotropy and the moisture content of the LMX reservoir on wellbore collapse pressure and wellbore integrity are investigated. The results show that shale strength, especially cohesion, is more sensitive to the influence of water. With the increase of water content, the inclination angle of the minimum value obtained by shale strength is deviated to the left, and the collapse pressure and instability area increase significantly. At the same time, it is necessary to adjust the direction of borehole drilling to avoid the occurrence of the zone of bedding slip instability in the direction of the minimum in situ stress, and the inversion of in situ stress should be corrected by considering the effect of bedding on the location of the maximum in situ stress. The study on the effects of bedding and water content on the instability zone can provide suggestions and guidance for the optimization of borehole trajectory, the control of bottom hole safety pressure, the inversion of in situ stress, and the drilling and completion of wells. [ABSTRACT FROM AUTHOR]

This paper focuses on a coordinated tracking planning method of multiple unmanned aerial vehicles (UAVs), which was deployed in the best positions to better fulfill the marine target localization tasks when approaching the target. The optimal planning of multi-UAVs was implemented using an online centralized nonlinear model predictive control (NMPC) based on the target state's uncertainty criteria. The penalty function is used to solve UAV platform dynamic performance in the model predictive control method to consider the more realistic situation. The coordinated planning problems of multi-UAVs are numerically simulated and compared with the Lyapunov vector field guidance (LVFG) method under classical mission scenarios. Simulation results demonstrate that the algorithm can maintain the optimal observation configuration of multi-UAVs to improve the marine target positioning accuracy, verifying the feasibility and superiority of this method. Furthermore, the simulation results can provide a useful reference for the flight control law design of multi-UAVs with optimal observation configuration. [ABSTRACT FROM AUTHOR]

The trajectory optimization design of interceptor is very important in the defense combat against a class of high-speed and strong-maneuvering aircraft. At present, an important idea is to use hp pseudospectral method to offline optimizes the trajectory of interceptor, but the solving efficiency of this method needs to be further improved. Aiming at this issue, an improved adaptive hp pseudospectral method is proposed in this paper. In order to shorten the solving time of the algorithm, the proposed method has two main improvements on the basis of the traditional hp pseudospectral method: on one hand, by judging the positions of the control sudden change points, prerefine the mesh around them according to certain rules. On the other hand, the curvature of the system state curve is used as the criterion to segment the original mesh nonuniformly so that more mesh points can be allocated where the curvature is large. These two points together ensure that the collocation point resources can be used more efficiently in the mesh refinement process. The simulation results show that the proposed method can solve the optimized trajectory of interceptor effectively, and it also proves that this method has higher solving efficiency than the traditional adaptive hp method. [ABSTRACT FROM AUTHOR]

Traffic flow optimization and trajectory guidance in merging zones have significant implications for improving capacity and reducing time consumption. The development of V2X communication provides new insights to solve this problem by tackling the information and releasing trajectories schemes. Therefore, this paper aims to discuss the trajectory management in the merging zone for ACC vehicles. A vehicle dispatching and car-following model is proposed to generate steady traffic flow first. An algorithm framework for consecutive traffic flow is presented with the idea of FIFO rules. Then, a two-step method for an individual vehicle is discussed in detail to compute a trajectory. The first step is to select and determine the priority of the optional gaps. The next step is to verify the options' feasibility, decide on the target gap, and output the trajectories to merge successfully. Numerical experiments validate that the proposed method guarantees safe driving and provides relatively smooth trajectories to the vehicles. Furthermore, increased capacity and higher velocity are observed in a comparative experiment. The cooperative optimization algorithm could be applied efficiently in practice and benefit from its rapid response and low computation complexity. [ABSTRACT FROM AUTHOR]

While the process of intelligent industrial production is accelerating, the application scope of welding robots is also expanding. For the purpose of reducing the work efficiency and time consumption of the welding robot, the ACO is used for the shortest distance and the GA is used for the shortest time fixed-point path trajectory optimization. The application of parameter optimization and random disturbance factor in the ACO increases the global search performance of the algorithm. In the shortest time trajectory optimization, the B-spline curve interpolation method and the GA are combined to carry out the segmental optimization processing. Simulation experiments show that the optimization strategy of ACO can increase the iterative calculation efficiency and path optimization performance of the algorithm. At the same time, the robot with optimized genetic algorithm has smaller fluctuations in joint angle and angular velocity in the simulated welding task, and the optimization algorithm takes 17.6 s less than the traditional particle swarm algorithm and 11 s less than the single A ∗ algorithm. The experiments confirmed the performance of the ACO-GA for the path optimization of the welding robot, and research can provide a scientific path optimization reference for the welding task of the industrial production line. [ABSTRACT FROM AUTHOR]

Capturing and stabilizing tumbling targets using dual-arm space robots are very crucial to on-orbit servicing task. However, it is still very challenging due to the complex dynamics coupling and closed-chain constraints between the manipulators, the base, and the target. In this paper, a kinodynamic trajectory optimization method is proposed to generate the motion of a dual-arm space robot for stabilizing the captured tumbling target, which is formulated and solved as a nonlinear programming problem using direct collocation. Instead of optimizing the trajectory of each joint with the dynamics model of space robot, this method optimizes the trajectory of the tumbling target while considering the kinematics and dynamics constraints between the two arms and the target simultaneously. The objective function of the optimization is defined as weighted detumbling time, base disturbance, and manipulability, in order to avoid singularity and save the energy of space robot for further manipulation. Several physical simulations are carried out to validate the proposed method. [ABSTRACT FROM AUTHOR]

For the vertical landing process of reusable rockets, the landing accuracy is likely to be affected by disturbances and faults during flight. In this paper, a fault-tolerant guidance method based on the MPC framework is put forward. First, we propose a piecewise guidance algorithm that combines a trajectory optimization algorithm based on convex optimization with the MPC framework. With the fast trajectory optimization algorithm and the MPC framework that recursively introduces the real-time state, this algorithm forms a robust closed loop. Then, we design an integrated guidance, navigation, and control (GNC) system to enhance the fault tolerance and robustness of the guidance method. Simulation experiments verify that this method is fault-tolerant to various fault conditions including navigation system failures, control system failures, drag coefficient deviations, and atmospheric density deviations. This guidance method is robust enough to overcome disturbances and faults, and it has great potential for online use. [ABSTRACT FROM AUTHOR]

This paper presents a trajectory optimization algorithm for super-synchronous-transfer-orbit (SSTO) large launch systems by convex optimization. The payload of SSTO launch systems is typically a geostationary equatorial orbit (GEO) satellite, and the time and position of orbital injection are constrained, which is quite different from the case of general satellites. In this paper, the optimal control problem of SSTO large launch systems is formulated considering the terminal constraints including orbital elements and the time-position equation. To improve the computational performance of the algorithm, the terminal orbital element constraints are expressed in the perifocal coordinate system with second-order equations. And then, several convexification techniques and their modified strategies are applied to transform the original trajectory optimization problem into a series of convex optimization problems, which can be solved iteratively with high accuracy and computational efficiency. Considering the time-position constraint of the payload, the flight time updater design method is proposed to correct the error of time during the flight, which lays solid foundation for the subsequent flight phase, guaranteeing that the GEO satellite settles into the required position. Finally, simulation results indicate the high efficiency and accuracy and strong robustness of the proposed algorithm in different special situations including engine failure and time delay. The algorithm proposed in this paper has great development potential and application prospect in onboard trajectory optimization of SSTO launch missions and similar situations. [ABSTRACT FROM AUTHOR]

Aiming at the problem of alignment deviation between shaft and hole caused by accumulated error in the assembly process of brake disc shaft hole, a trajectory planning method for compensating accumulated error is proposed. First, the path before the error is planned, and then the second compensation path is planned between the error position and the actual target point, so as to realize the accurate assembly of the brake disc. In this paper, the IRB 1410 robot is taken as the research object, and its kinematic model is established by using the improved D-H parameter method. The joint space quintic B-spline interpolation method was used to carry out trajectory planning, and the improved particle swarm optimization algorithm was introduced to solve the optimization. The optimal time and smooth trajectory were expected to be obtained. Then, using MATLAB software to simulate, compared with the nonoptimized trajectory, not only is the trajectory running time reduced from 8.6 s to 6.7 s but also the maximum joint change angle of each joint is reduced, which proves that the algorithm has optimization effect on trajectory running time and stability. Finally, the accuracy verification experiment of the algorithm is carried out, and the error between simulation and experiment is less than 6%, which shows the effectiveness of the method. This research provides a theoretical basis for improving the responsiveness and stability of brake disc assembly. [ABSTRACT FROM AUTHOR]

The rapid development of V2X communication has made it possible to optimize and control the trajectories of vehicles from the whole traffic flow's perspective and improve traffic performance. Therefore, this paper discusses the trajectories management problem on highway facilitated with lanes exclusively for autonomous vehicles (AVs). The paper proposes a model that aims to search for optimal trajectories and minimize total travel time for AVs with multiple initial and target states while averting crashes and conforming to vehicles' kinetic. Dividing the time zone into discrete pieces, the model is analyzed as a large-scale discrete problem influenced by the randomness of the sequence of vehicles. A two-phase algorithm combined with upper evolution strategies and lower dynamic programming is developed to diminish stochastics and reduce computation step by step and solve the trajectories optimization model. Numerical experiments validate that the proposed method is capable of generating optimal trajectories for multiple AVs and approaching to system optimum by simultaneously solving all the spatial and temporal values of the trajectories. The two-phase algorithm can be applied efficiently in practice to obtain a feasible approximate solution for trajectories optimization by presetting appropriate algorithm parameters. [ABSTRACT FROM AUTHOR]

This paper presents a constrained connected automated vehicles (CAVs) trajectory optimization method on curved roads with infrastructure assistance. Specifically, this paper systematically formulates trajectory optimization problems in a spatial domain and a curvilinear coordinate. As an alternative of temporal domain and Cartesian coordinate formulation, our formulation provides the constrained trajectory optimization flexibility to describe complex road geometries, traffic regulations, and road obstacles, which are usually spatially varying rather than temporal varying, with assistances vehicle to infrastructure (V2I) communication. Based on the formulation, we first conducted a mathematical proof on the controllability of our system, to show that our system can be controlled in the spatial domain and curvilinear coordinate. Further, a multiobjective model predictive control (MPC) approach is designed to optimize the trajectories in a rolling horizon fashion and satisfy the collision avoidances, traffic regulations, and vehicle kinematics constraints simultaneously. To verify the control efficiency of our method, multiscenario numerical simulations are conducted. Suggested by the results, our proposed method can provide smooth vehicular trajectories, avoid road obstacles, and simultaneously follow traffic regulations in different scenarios. Moreover, our method is robust to the spatial change of road geometries and other potential disturbances by the road curvature, work zone, and speed limit change. [ABSTRACT FROM AUTHOR]

Aiming at the controllability of spin-stabilized projectile trajectory correction, a new two-dimensional trajectory correction projectile model with a controllable air-ducts structure suitable for the spin-stabilized projectile is proposed in this paper. Furthermore, control strategies of the projectile in the corrected configuration are studied to ensure a stable flight. The correction scheme of the projectile is innovated on the basis of the ram air control mechanism. The air-ducts structure is designed inside the projectile body, and the internal air valve is used to control the lateral air-jet to achieve trajectory correction of the projectile. This is a new two-dimensional trajectory correction scheme with a relatively simple control method. Firstly, the correction mechanism of the new air-ducts structure projectile is analyzed. Secondly, based on the dynamic equation of the projectile, the key parameters of the impulse air valve control, including the safe range of the working pulse width and frequency, are calculated, and the corresponding control strategies are proposed. Finally, the flow field of the projectile in the corrected configuration of the terminal trajectory is numerically simulated, and aerodynamic parameters of the projectile are obtained. Through stability conditions established in this paper and combined with aerodynamic parameters, the validity of the proposed projectile stable flight control strategies is confirmed. The innovations of this paper include: (1) a proposed new aerodynamic configuration model with the air-ducts structure for the spin-stabilized projectile and (2) proposed innovative stable flight control strategies of the corrected configuration projectile. The numerical simulation results show that, compared with the reference projectile without air-ducts structure, the lateral force of the air-ducts structure projectile can produce a radial correction effect on the moving projectile. The simulation results of control strategies indicate that the control strategies can ensure stable flight of the corrected configuration projectile under different conditions. [ABSTRACT FROM AUTHOR]

In recent years, there has been widespread interest in the design of microair vehicles (MAVs) for flapping flight with high-aspect ratio wings due to their high efficiency and energy savings. However, the flexibility of a flapping wing causes the aeroelastic effect, which remains a subject of investigation. Generally, existing research simulates active bending and twisting of flexible wings under the assumption of neglecting flapping inertia. In this research, the kinematic optimization of a bionic wing with passive deformation in forward flight while undergoing flapping and pitching is considered. To this end, a computational aeroelasticity framework, which includes the three-dimensional unsteady vortex lattice method (UVLM) and the Newmark-β method, is constructed for flapping flight. Under the assumption of linear elastic deformation, this tool is capable of simulating attached flows over a thin wing and capturing unsteady effects of wakes. A bionic numerical wing with an aspect ratio of 6.5, chord Reynolds number of 1.9 × 105, and reduced frequency less than 0.1 is investigated in kinematic optimization. The computational aeroelasticity framework is combined with a global optimization algorithm to identify the optimal kinematics that maximize the propulsive efficiency under the minimum average lift constraint. Two types of numerical wings, rigid wing and flexible wing, are considered here to compare the influence of deformation on the aerodynamics of the flapping wing. The results show that the aeroelastic effect, which increases the flapping amplitude, yields a significant improvement in terms of propulsive efficiency. In addition, the optimization algorithm maximizes the thrust efficiency while satisfying the required lift. Moreover, the optimal kinematics of both the rigid wing and the flexible wing reach the maximum flapping angle, which indicates that a larger range of motions is needed for optimal kinetics when loosening the boundary conditions. [ABSTRACT FROM AUTHOR]

Work zone areas are frequent congested sections considered as the freeway bottleneck. Connected and autonomous vehicle (CAV) trajectory optimization can improve the operating efficiency in bottleneck areas by harmonizing vehicles' manipulations. This study presents a joint trajectory optimization of cooperative lane changing, merging, and car-following actions for CAV control at a local merging point together with upstream points. The multiagent reinforcement learning (MARL) method is applied in this system, with one agent providing a merging advisory service at the merging point and controlling the inner-lane vehicles' headway for smooth outer-lane vehicle merging, while other agents provide lane-changing advisory services at advance lane-changing points to control how vehicles make lane changes in advance and perform corresponding headway adjustment, similar to and jointly with the merging advisory service. Uniting all agents, the coordination graph (CG) method is applied to seek the global optimum, overcoming the exponential growth problem in MARL. Using MATLAB and the VISSIM COM interface, an online simulation platform is established. The simulation results show that MARL is effective for online computation with in-timing response. More importantly, comparisons of the results obtained in various scenarios demonstrate that the proposed system obtained smoother vehicle trajectories in all controlled sections, rather than only in the merging area, indicating that it can achieve better traffic conditions in freeway work zone areas. [ABSTRACT FROM AUTHOR]

Periodic cruise has the potential to improve the fuel-saving efficiency of hypersonic cruise vehicles but is difficult to optimize. In this paper, hypersonic periodic cruise trajectory is analyzed theoretically and optimized by an improved Particle Swarm Optimization algorithm. Firstly, through theoretical analysis, it is determined that the optimal throttle curve can be parameterized as a switching function. Considering the optimization direction of algorithm, a new penalty function for the constraints of periodic cruise is proposed. Then, PSO algorithm is improved and applied in periodic cruise trajectory optimization. Numerical results demonstrate that optimized periodic cruise trajectory costs less fuel compared with steady-state cruise trajectory, and without computing gradient information, the proposed method is also robust. Finally, the fuel-saving mechanism of periodic cruise is explored by comparing with steady-state cruise, which reveals that periodic cruise trajectory has higher impulse and lift-drag ratio, but lower mechanical energy loss rate. [ABSTRACT FROM AUTHOR]

The increasing demand for environmentally friendly and passenger-favored flight operation requires a systematic scheme of sustainable trajectory optimization for the aircraft cruise. This paper achieves it by proposing an innovative performance framework based on the comprehensive benefit to the society considering both economic and noneconomic ones, following which the sustainable trajectory optimization problem is modeled by discretization. A method combining forward recurrence and memoization operation, called memoization dynamic programming, is developed to solve the model with computational efficiency. Working with real-world operational data of a typical flight route, we demonstrate the effectiveness of the proposed scheme at different levels and explore the difference in its performance due to meteorological conditions, aircraft type, and time horizon. The scheme is proved to perform robustly in comprehensive performance with a stable benefit rate of about 8% through sensitivity analysis, by which we find that it is relatively better for the flights cruising on business route with a load factor of 85%. Tradeoff results suggest that the systematic consideration of both the economic and noneconomic performance contributes to improved integrated sustainability. In particular, the optimal comprehensive performance at a monthly level can be obtained when accepting an additional $26,500 economic cost. [ABSTRACT FROM AUTHOR]

Periodic cruise has the potential to improve the fuel-saving efficiency of hypersonic cruise vehicle but is difficult to optimize. In this paper, a two-level optimization method for the trajectory of periodic cruise is proposed. Due to that the periodic cruise trajectory can be divided into an acceleration phase where engine works and a glide phase where engine is off, the two-level optimization method is proposed to optimize the trajectory in each phase by the corresponding level. In the first level, Downhill Simplex Method (DSM) is employed to find an optimal angle of attack in the acceleration phase. Subsequently, the optimal trajectory in glide phase is obtained by the Pseudo-Spectral Method (PSM) in the second optimization level. Numerical results demonstrate the effectiveness of the proposed method. Finally, through comparing with steady-state cruise, it is concluded that periodic cruise makes full use of the change of atmospheric density and lift-drag ratio; thus, fuel saving is achieved. [ABSTRACT FROM AUTHOR]

In a low-visibility environment, the speed of traffic flow is more discrete on highways, which easily causes traffic accidents. To improve the safety and efficiency level of low-visibility zones on highways, a comprehensive optimization control method is proposed. The method uses formations of a low-visibility zone to queue discrete vehicles from the upstream intersection. Then, according to the relationship between the arrival time of the fleet and the phase state of the intersection, speed guidance and trajectory optimization are carried out to improve the traffic efficiency of the fleet that enters the low-visibility zone. Finally, a low-visibility zone of a highway segment is analysed with different traffic flows for the main road and the secondary roads, and the results show that the proposed optimization control method can prevent trajectory overlap and effectively decrease traffic delays on highways. [ABSTRACT FROM AUTHOR]

In this paper, an offline hybrid trajectory optimization approach is proposed for variable-sweep missiles to explore the superiority in the diving phase. Aiming at the maximal terminal velocity with the impact angle constraint, the trajectory optimization model is formulated under multiple constraints, and the aerodynamic analysis in different sweep angles is discussed. Unlike only the attack angle used for the optimization process traditionally, the two-variable optimization scheme on both the attack angle and sweep angle is investigated for variable-sweep missiles. Then, the trajectory optimization problem is transformed into the nonlinear programming problem via a hybrid optimization strategy combining the Gauss pseudospectral method and direct shooting method to obtain the high precision and fast convergence solution. Finally, to verify the feasibility of the optimal trajectory under uncertainties, the tracking guidance law is designed on basis of the gain scheduled linear quadratic regulator control. Numerical simulation results reveal not only of the proposed hybrid optimization strategy but also of the superiority of variable-sweep missiles compared with traditional missiles. [ABSTRACT FROM AUTHOR]

In this paper, a trajectory optimization strategy for the hypersonic morphing aircraft is proposed, and the AMPI method is used to generate the online trajectory with initial state errors. Firstly, the aerodynamic model and propulsion model of the hypersonic morphing aircraft were established considering the wingspan and the scramjet. Secondly, the optimization strategy was proposed via Gauss pseudospectral method considering the control variables including angle of attack (AOA) and wingspan. The optimized trajectory met the final constraints and path constraints with the objective to minimize the time of the ascent phase. Then, the AMPI method was used to generate online trajectory without solving OCP or NLP on the base of trajectory database calculated by the optimization strategy. The simulation results indicate high accuracy of AMPI method and the final errors corresponding to different initial errors were acceptable. The mean value of the CPU time of the method was about 0.1 second, which shows real-time capability. [ABSTRACT FROM AUTHOR]

The trajectory information generated by the moving object plays an important role in studying the object movement. In this paper, a trajectory data compression algorithm based on the motion state changing is proposed to reduce trajectory data storage space and increase compression speed, which can accurately show the motion state and trajectory characteristics. This study has certain significance for the exploration of mass traffic data and the planning of traffic network. Combining the angle threshold with the velocity threshold of a moving object, the key data points are found and the redundant information is removed. Subsequently, the compressed trajectory is obtained. The experimental results show that the new algorithm can help to improve compression efficiency. The compressed trajectory has high similarity with the original trajectory in movement tendency. [ABSTRACT FROM AUTHOR]

This paper researches the ascent trajectory optimization problem in view of multiple constraints that effect on the launch vehicle. First, a series of common constraints that effect on the ascent trajectory are formulated for the trajectory optimization problem. Then, in order to reduce the computational burden on the optimal solution, the restrictions on the angular momentum and the eccentricity of the target orbit are converted into constraints on the terminal altitude, velocity, and flight path angle. In this way, the requirement on accurate orbit insertion can be easily realized by solving a three-parameter optimization problem. Next, an improved particle swarm optimization algorithm is developed based on the Gaussian perturbation method to generate the optimal trajectory. Finally, the algorithm is verified by numerical simulation. [ABSTRACT FROM AUTHOR]

A hybrid double-loop optimization algorithm combing particle swarm optimization (PSO) and nonintrusive polynomial chaos (NIPC) is proposed for solving the robust trajectory optimization of hypersonic glide vehicle (HGV) under uncertainties. In the outer loop, the PSO method searches globally for the robust optimal control law according to a penalized fitness function that contains the system robustness considerations. In the inner loop, uncertainty propagation of the stochastic system is performed using the NIPC method, to provide statistical moments for the iterative scheme of the PSO method in the outer loop. Only control variables are discretized, and the state constraints are satisfied implicitly through the numerical integration process, which reduces the number of decision variables as well as the huge amount of computation increased by NIPC. In the end, the robust optimal control law is achieved conveniently. Numerical simulations are carried out considering a classical time-optimal trajectory optimization problem of HGV with uncertainties in both initial states and aerodynamic coefficients. The results demonstrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Lunar exploration architecture can be made more flexible and reliable with the support of a low-Earth orbit (LEO) space station. This study therefore evaluated a proposed hybrid optimization scheme to design the entire trajectory of a reusable spacecraft starting from trans-Earth injection (EI) at the perilune and ending at an LEO space station. As such a trajectory has multiple constraints and multiple dynamical models, it is divided into the trans-Earth phase, aerocapture phase, and postatmospheric phase. The optimization scheme is performed at two levels: sublevel and top level. At the sublevel, two novel pseudo rules are proposed to optimize the trans-Earth trajectory so that it satisfies the coplanar constraints of the space station. Then, in the aerocapture phase, the bank angle is optimized to satisfy the mission constraints, and in the atmospheric phase, the one-impulsive maneuver is performed and optimized to insert the spacecraft into the target space station orbit. The multiple phases are connected to each other by boundary conditions where the terminal state of the previous phase is transformed into the initial state of the following phase. At the top level, the vacuum perigee height is selected as the mission design variable based on problem characteristics analysis and a hybrid optimization scheme is conducted to minimize the total velocity increment. The simulation results demonstrate that the proposed hybrid optimization method is effective for the design of an entire trajectory with acceptable velocity cost which is less than that in the previous study. The coplanar constraints of the space station and other mission constraints in each phase are also satisfied. Furthermore, the proposed trajectory design method is shown to be applicable to a reusable spacecraft returning to an LEO space station parked in any arbitrary orbital plane. [ABSTRACT FROM AUTHOR]

It is agreed that connected vehicle technologies have broad implications to traffic management systems. In order to alleviate urban congestion and improve road capacity, this paper proposes a multilane spatiotemporal trajectory optimization method (MSTTOM) to reach full potential of connected vehicles by considering vehicular safety, traffic capacity, fuel efficiency, and driver comfort. In this MSTTOM, the dynamic characteristics of connected vehicles, the vehicular state vector, the optimized objective function, and the constraints are formulated. The method for solving the trajectory problem is optimized based on Pontryagin's maximum principle and reinforcement learning (RL). A typical scenario of intersection with a one-way 4-lane section is measured, and the data within 24 hours are collected for tests. The results demonstrate that the proposed method can optimize the traffic flow by enhancing vehicle fuel efficiency by 32% and reducing pollutants emissions by 17% compared with the advanced glidepath prototype application (GPPA) scheme. [ABSTRACT FROM AUTHOR]

It is agreed that connected vehicle technologies have broad implications to traffic management systems. In order to alleviate urban congestion and improve road capacity, this paper proposes a multilane spatiotemporal trajectory optimization method (MSTTOM) to reach full potential of connected vehicles by considering vehicular safety, traffic capacity, fuel efficiency, and driver comfort. In this MSTTOM, the dynamic characteristics of connected vehicles, the vehicular state vector, the optimized objective function, and the constraints are formulated. The method for solving the trajectory problem is optimized based on Pontryagin's maximum principle and reinforcement learning (RL). A typical scenario of intersection with a one-way 4-lane section is measured, and the data within 24 hours are collected for tests. The results demonstrate that the proposed method can optimize the traffic flow by enhancing vehicle fuel efficiency by 32% and reducing pollutants emissions by 17% compared with the advanced glidepath prototype application (GPPA) scheme. [ABSTRACT FROM AUTHOR]

In order to realize the concept of air traffic sustainable operation, taking the aircraft climbing stage as an example, firstly, we establish the vertical trajectory model of aircraft climbing, analyze the change rule of aircraft performance parameters under different indicated airspeed, and establish the RTA and RHA constraint models according to the waypoint constraints. Then, considering the fuel economy and the greenhouse effect of pollutant emission, we establish a multiobjective model of aircraft flight parameter optimization, and, based on the multiobjective genetic algorithm, we establish an optimization model. Finally, we use B737-800 aircraft to carry out simulation experiments and find that, with the change of speed, fuel consumption and warming trend are different, and "objective weight, aircraft mass, flight distance, RTA time window, and wind" have different effects on the optimization results. The results show that this optimization method has a good compromise between fuel consumption and greenhouse effect by changing the weighting factor. By optimizing the flight parameters of the aircraft, it can effectively reduce the impact on the environment and provide theoretical support for the green flight of the aircraft. [ABSTRACT FROM AUTHOR]

In order to make an accurate prediction of vehicle trajectory in a dynamic environment, a Unidirectional and Bidirectional LSTM (UB-LSTM) vehicle trajectory prediction model combined with behavior recognition is proposed, and then an acceleration trajectory optimization algorithm is proposed. Firstly, the interactive information with the surrounding vehicles is obtained by calculation, then the vehicle behavior recognition model is established by using LSTM, and the vehicle information is input into the behavior recognition model to identify vehicle behavior. Then, the trajectory prediction model is established based on Unidirectional and Bidirectional LSTM, and the identified vehicle behavior and the input information of the behavior recognition model are input into the trajectory prediction model to predict the horizontal and vertical speed and coordinates of the vehicle in the next 3 seconds. Experiments are carried out with NGSIM data sets, and the experimental results show that the mean square error (MSE) between the predicted trajectory and the actual trajectory obtained by this method is 0.124, which is 97.2% lower than that of the method that does not consider vehicle behavior and directly predicts the trajectory. The test loss is 0.000497, which is 95.68% lower than that without considering vehicle behavior. The predicted trajectory is obviously optimized, closer to the actual trajectory, and the performance is more stable. [ABSTRACT FROM AUTHOR]

Trajectory optimization problem for hypersonic vehicles has long been recognized as a difficult problem. This paper brings control constraints into the trajectory optimization to make the optimal trajectory meet the requirements of control performance. The strong nonlinear characteristic of the ascent phase aerodynamics makes the trajectory optimization problem difficult to be solved by the optimal control theory. A trajectory optimization algorithm based on the improved pigeon-inspired optimization (PIO) algorithm is proposed to solve the complex trajectory optimization problem under multiple constraints. To overcome the obstacle of premature convergence and deceptiveness, the evolutionary strategy of qubit in quantum evolutionary algorithm (QEA) is introduced into the PIO to maintain population diversity and judge the optimal solution. To handle constraints, the penalty function is used to construct the fitness function. The optimal ascent trajectory is obtained by utilizing the improved PIO algorithm. Then, the trajectory inverse algorithm is used to verify the feasibility of the optimal trajectory to ensure that a feasible optimal trajectory is obtained. The comparison results show that the proposed algorithm outperforms particle swarm optimization (PSO) and standard PIO on trajectory optimization. Meanwhile, the simulation result shows that the performance of the optimal ascent trajectory with control constraints is improved and the trajectory is feasible. Therefore, the method is potentially feasible for solving the ascent trajectory optimization problem under control constraint for hypersonic vehicles. [ABSTRACT FROM AUTHOR]

This paper presents a novel method of dynamic modeling and design optimization integrated with dynamics for parallel robot manipulators. Firstly, a computationally efficient modeling method, the discrete time transfer matrix method (DT-TMM), is proposed to establish the dynamic model of a 3-PRR planar parallel manipulator (PPM) for the first time. The numerical simulations are performed with both the proposed DT-TMM dynamic modeling and the ADAMS modeling. The applicability and effectiveness of DT-TMM in parallel manipulators are verified by comparing the numerical results. Secondly, the design parameters of the 3-PRR parallel manipulator are optimized using the kinematic performance indices, such as global workspace conditioning index (GWCI), global condition index (GCI), and global gradient index (GGI). Finally, a dynamic performance index, namely, driving force index (DFI), is proposed based on the established dynamic model. The described motion trajectory of the moving platform is placed into the optimized workspace and the initial position is determined to finalize the end-effector trajectory of the parallel manipulator by the further optimization with the integrated kinematic and dynamic performance indices. The novelty of this work includes (1) developing a new dynamic model method with high computation efficiency for parallel robot manipulators using DT-TMM and (2) proposing a new dynamic performance index and integrating the dynamic index into the motion and design optimization of parallel robot manipulators. [ABSTRACT FROM AUTHOR]

At present, two kinds of shortages exist in the research on cooperative combat. One is that radar detection threat (which cannot be ignored) is rarely considered. The other is that limited efforts have been made on the cooperative penetration trajectories under the conditions of long distance, vast airspace, and wide speed range. In order to offset the shortages of the research on cooperative combat, the penetration trajectory optimization method considering the influence of aircraft radar cross-section (RCS) and the cooperative penetration strategy is proposed in this study. Firstly, the RCS data are calculated by the physical optics (PO) method. The radar detection threat model is established considering the influence of the aircraft RCS. Then, a trajectory optimization framework with the dynamic model, constraint conditions, and optimal objectives is formed. Using the hp-adaptive Radau pseudospectral method, the optimal control problem for a single aircraft flight is solved. Finally, a cooperative penetration strategy is proposed to solve the cooperative penetration problem of multiaircraft. The impact time and angle constraints are given, and the virtual target point is introduced for terminal guidance. Two cases are simulated and verified. Simulation results demonstrate that the proposed method is effective. The single aircraft can effectively penetrate, and the multiaircraft can fulfill the requirement of cooperative impact time and angle under the condition of meeting the minimum threat of radar detection. [ABSTRACT FROM AUTHOR]

At present, two kinds of shortages exist in the research on cooperative combat. One is that radar detection threat (which cannot be ignored) is rarely considered. The other is that limited efforts have been made on the cooperative penetration trajectories under the conditions of long distance, vast airspace, and wide speed range. In order to offset the shortages of the research on cooperative combat, the penetration trajectory optimization method considering the influence of aircraft radar cross-section (RCS) and the cooperative penetration strategy is proposed in this study. Firstly, the RCS data are calculated by the physical optics (PO) method. The radar detection threat model is established considering the influence of the aircraft RCS. Then, a trajectory optimization framework with the dynamic model, constraint conditions, and optimal objectives is formed. Using the hp-adaptive Radau pseudospectral method, the optimal control problem for a single aircraft flight is solved. Finally, a cooperative penetration strategy is proposed to solve the cooperative penetration problem of multiaircraft. The impact time and angle constraints are given, and the virtual target point is introduced for terminal guidance. Two cases are simulated and verified. Simulation results demonstrate that the proposed method is effective. The single aircraft can effectively penetrate, and the multiaircraft can fulfill the requirement of cooperative impact time and angle under the condition of meeting the minimum threat of radar detection. [ABSTRACT FROM AUTHOR]

In this paper, a recent physics-based metaheuristic algorithm, the Colliding Bodies Optimization (CBO), already employed to solve problems in civil and mechanical engineering, is proposed for the optimization of interplanetary trajectories by using both indirect and direct approaches. The CBO has an extremely simple formulation and does not depend on any initial conditions. To test the performances of the algorithm, missions with remarkably different orbital transfer energies are considered: from the simple planar case, as the Earth-Mars orbital transfer, to more energetic ones, like a rendezvous with the asteroid Pallas. [ABSTRACT FROM AUTHOR]

In this work, the concept of a multipurpose mission that can explore both the Moon and Mars with a single launch is proposed, and potential launch opportunities are analyzed to establish an early-phase trajectory concept. The proposed mission applies the concept of a piggyback ride to a small-sized lunar probe, i.e., the daughtership, of the main Mars orbiter, i.e., the mothership. For the trajectory design, the Earth-Moon-Mars gravity assist (EMMGA) trajectory is adopted for the mothership to reach Mars, and the daughtership is assumed to be released from the mothership during lunar flyby. To investigate the early-phase feasibility of the proposed mission, the launch windows have been analyzed and the associated delta-Vs have been directly compared with the solutions obtained for typical Earth-Mars direct (EMD) transfer options. The identified launch windows (in the years 2031 and 2045) could be the strongest candidates for the proposed conceptual mission. Under the current assumptions, up to approximately 15% (in 2031) and 9% (in 2045), more dry mass is expected to be delivered to Mars by appropriately selecting one of the currently available launch vehicles, regardless of whether the EMMGA transfer option is used. For missions around the Moon using a SmallSat in 2031, the feasibility of a lunar orbiter case and an impactor case is briefly analyzed based on the delta-Vs required to divert the SmallSat from the mothership. Although the current work is performed under numerous assumptions for a simplified problem, the narrowed candidate launch window from the current work represents a good starting point for more detailed trajectory design optimization and analysis to realize the proposed conceptual mission. [ABSTRACT FROM AUTHOR]

The minimum time interception problem with a tangent impulse whose direction is the same as the satellite's velocity direction is studied based on the relative motion equations of elliptical orbits by the combination of analytical, numerical, and optimization methods. Firstly, the feasible domain of the true anomaly of the target under the fixed impulse point is given, and the interception solution is transformed into a univariate function only with respect to the target true anomaly by using the relative motion equation. On the basis of the above, the numerical solution of the function is obtained by the combination of incremental search and the false position method. Secondly, considering the initial drift when the impulse point is freely selected, the genetic algorithm-sequential quadratic programming (GA-SQP) combination optimization method is used to obtain the minimum time interception solution under the tangent impulse in a target motion cycle. Thirdly, under the high-precision orbit prediction (HPOP) model, the Nelder-Mead simplex method is used to optimize the impulse velocity and transfer time to obtain the accurate interception solution. Lastly, the effectiveness of the proposed method is verified by simulation examples. [ABSTRACT FROM AUTHOR]

The evasion maneuver problem of hypersonic vehicles differs from those of ballistic missiles and other traditional weapons, showing distinctive properties including expansive maneuver range and weak maneuverability. How to avoid the disadvantage of low available overload and ensure follow-up tasks are the main concerns of the hypersonic penetration. This paper presents a penetration trajectory optimization algorithm for an air-breathing hypersonic vehicle, where the prerequisite penetration condition is analyzed and control costs are chosen as an objective function to minimize the fuel consumption and maneuver range. This paper focuses on how to formulate the complex, highly constrained nonconvex penetration problem to be a sequence of easily solved second-order cone programming through a combination of successive linearization and relaxation techniques. Innovation lies in the raising of the penetration angle and the relaxation technique of nonlinear and nonconvex elements. Various numerical simulations are conducted to verify the validity of penetration condition and to demonstrate that the proposed method is effective and has a good computational performance irrespective of initial guesses. [ABSTRACT FROM AUTHOR]

A novel sequential convex (SCvx) optimization scheme via the Chebyshev pseudospectral method is proposed for efficiently solving the hypersonic reentry trajectory optimization problem which is highly constrained by heat flux, dynamic pressure, normal load, and multiple no-fly zones. The Chebyshev-Gauss Legend (CGL) node points are used to transcribe the original dynamic constraint into algebraic equality constraint; therefore, a nonlinear programming (NLP) problem is concave and time-consuming to be solved. The iterative linearization and convexification techniques are proposed to convert the concave constraints into convex constraints; therefore, a sequential convex programming problem can be efficiently solved by convex algorithms. Numerical results and a comparison study reveal that the proposed method is efficient and effective to solve the problem of reentry trajectory optimization with multiple constraints. [ABSTRACT FROM AUTHOR]

Solar sails have many advantages over traditional chemical propulsion spacecraft, such as needlessness of fuel, high payload ratio, long service life, and great application potential in deep space exploration, interstellar voyage, and other aerospace application fields. However, the period of solar sail transfer from the initial orbit to the desired orbit is relatively long. Thus, it is necessary to optimize the transfer trajectory of solar sail according to specific tasks. The hp-adaptive pseudospectral method combines the global pseudospectral method with the finite element method, which adopts double layer optimization strategy to solve the optimal control problem and has higher computational efficiency and accuracy than the traditional global pseudospectral method. In this paper, the pressure of solar light acting on the solar sail is analyzed, and the kinematic equation of the solar sail is established in polar coordinate system first; then the basic principle of the hp-adaptive pseudospectral method is introduced, and the steps of solving the transfer trajectory optimization problem by hp-adaptive pseudospectral method are proposed; finally, the trajectory optimization of the solar sail from Earth orbit to Sun-centered Mars orbit is simulated as an example to demonstrate the effectiveness of hp-adaptive pseudospectral method in the orbit transfer optimization problem of solar sail. The simulation results show that the adopted method is not sensitive to the initial values and has more reasonable distribution and less computational cost than the Gauss pseudospectral method. [ABSTRACT FROM AUTHOR]

This paper presents the problem of robust finite-time H∞ control with transients for ocean surface vessels equipped with dynamic positioning (DP) system in presence of input delay. The main objective of this work is to design a finite-time H∞ state feedback controller, which ensures that all states of ship do not exceed a given threshold over a fixed time interval, with better robustness and transient performance subject to time-varying disturbance. Based on a novel augmented Lyapunov-Krasovskii-like function (LKLF) with triple integral terms and a method combining the Wirtinger inequality and reciprocally convex approach, a less conservative result is derived. In particular, an H∞ performance index with nonzero initial condition is introduced to attenuate the overconservatism caused by the assumption of zero initial condition and enhance the transient performance of ship subject to external disturbance. More precisely, the controller gain matrix for the DP system can be achieved by solving the linear matrix inequalities (LMIs), which can be easily facilitated by using some standard numerical packages. Finally, a numerical simulation for a ship is proposed to verify the effectiveness and less conservatism of the controller we designed. [ABSTRACT FROM AUTHOR]

Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods. [ABSTRACT FROM AUTHOR]

By taking account of double-wishbone independent suspension with two unequal-length arms, the coordinate values of articulated geometry are based on structural limitations and constraint equations of alignment parameters. The sensitivities of front wheel alignment parameters are analyzed using the space analytic geometry method with insight module in ADAMS® software. The multiobjective optimization functions are designed to calculate the coordinate values of hardpoints with front suspension since the effect of time delay due to wheelbase can be easily obtained by vehicle speed. The K&C characteristics have been investigated using GA solutions in the simulation environment. The camber angle decreases from 1.152° to 1.05° and toe-in angle reduces from 1.036° to 0.944°. The simulation results demonstrate that the suggested optimization method is able to satisfy the suspension motion to enhance ride comfort. Experimental results, obtained by K&C test bench, also indicate that the optimized suspension can track the desired trajectory while keeping the vehicle performance in various road conditions. [ABSTRACT FROM AUTHOR]

Reentry trajectory optimization has been researched as a popular topic because of its wide applications in both military and civilian use. It is a challenging problem owing to its strong nonlinearity in motion equations and constraints. Besides, it is a high-dimensional optimization problem. In this paper, an improved chicken swarm optimization (ICSO) method is proposed considering that the chicken swarm optimization (CSO) method is easy to fall into local optimum when solving high-dimensional optimization problem. Firstly, the model used in this study is described, including its characteristic, the nonlinear constraints, and cost function. Then, by introducing the crossover operator, the principles and the advantages of the ICSO algorithm are explained. Finally, the ICSO method solving the reentry trajectory optimization problem is proposed. The control variables are discretized at a set of Chebyshev collocation points, and the angle of attack is set to fit with the flight velocity to make the optimization efficient. Based on those operations, the process of ICSO method is depicted. Experiments are conducted using five algorithms under different indexes, and the superiority of the proposed ICSO algorithm is demonstrated. Another group of experiments are carried out to investigate the influence of hen percentage on the algorithm’s performance. [ABSTRACT FROM AUTHOR]

Multiobjective trajectory optimization and adaptive backstepping control method based on recursive fuzzy wavelet neural network (RFWNN) are proposed to solve the problem of dynamic modeling uncertainties and strong external disturbance of the rubber unstacking robot during recycling process. First, according to the rubber viscoelastic properties, the Hunt-Crossley nonlinear model is used to construct the robot dynamics model. Then, combined with the dynamic model and the recycling process characteristics, the multiobjective trajectory optimization of the rubber unstacking robot is carried out for the operational efficiency, the running trajectory smoothness, and the energy consumption. Based on the trajectory optimization results, the adaptive backstepping control method based on RFWNN is adopted. The RFWNN method is applied in the main controller to cope with time-varying uncertainties of the robot dynamic system. Simultaneously, an adaptive robust control law is developed to eliminate inevitable approximation errors and unknown disturbances and relax the requirement for prior knowledge of the controlled system. Finally, the validity of the proposed control strategy is verified by experiment. [ABSTRACT FROM AUTHOR]

In order to improve the optimization accuracy and convergence rate for trajectory optimization of the air-to-air missile, a multi-interval mesh refinement Radau pseudospectral method was introduced. This method made the mesh endpoints converge to the practical nonsmooth points and decreased the overall collocation points to improve convergence rate and computational efficiency. The trajectory was divided into four phases according to the working time of engine and handover of midcourse and terminal guidance, and then the optimization model was built. The multi-interval mesh refinement Radau pseudospectral method with different collocation points in each mesh interval was used to solve the trajectory optimization model. Moreover, this method was compared with traditional h method. Simulation results show that this method can decrease the dimensionality of nonlinear programming (NLP) problem and therefore improve the efficiency of pseudospectral methods for solving trajectory optimization problems. [ABSTRACT FROM AUTHOR]