Search

A Runge-Kutta type method for directly solving special fourth-order ordinary differential equations (ODEs) which is denoted by RKFD method is constructed. The order conditions of RKFD method up to order five are derived; based on the order conditions, three-stage fourth- and fifth-order Runge-Kutta type methods are constructed. Zero-stability of the RKFD method is proven. Numerical results obtained are compared with the existing Runge-Kutta methods in the scientific literature after reducing the problems into a system of first-order ODEs and solving them. Numerical results are presented to illustrate the robustness and competency of the new methods in terms of accuracy and number of function evaluations. [ABSTRACT FROM AUTHOR]

Internal model control (IMC) design method based on quasi-LPV (Linear Parameter Varying) system is proposed. In this method, the nonlinear model is firstly transformed to the linear model based on quasi-LPV method; then, the quadrotor nonlinear motion function is transformed to transfer function matrix based on the transformation model from the state space to the transfer function; further, IMC is designed to control the controlled object represented by transfer function matrix and realize quadrotor trajectory tracking. The performance of the controller proposed in this paper is tested by tracking for three reference trajectories with drastic changes. The simulation results indicate that the control method proposed in this paper has stronger robustness to parameters uncertainty and disturbance rejection performance. [ABSTRACT FROM AUTHOR]

A meshfree modeling technique of material flow in the three-dimensional multiphysics thermomechanical friction stir welding process is presented. In this numerical model, the discretization in space is derived by the Element-Free Galerkin method using a Lagrangian meshfree convex approximation. The discrete thermal and mechanical equations are weakly coupled as the time advances using a forward difference scheme. A mortar contact algorithm is employed to model the stirring effect and heat generation due to frictional contact. Heat conductance between contacting bodies is considered as a function of contact pressure. A two-way adaptive procedure is introduced to the coupled thermomechanical system to surpass potential numerical problems associated with the extensive material deformation and spatial discretization. In each adaptive phase, a consistent projection operation utilizing the first-order meshfree convex approximation is performed to remap the solution variables. Finally, a three-dimensional multiphysics thermomechanical coupled friction stir welding problem is analyzed to demonstrate the effectiveness of the present meshfree numerical procedure. [ABSTRACT FROM AUTHOR]

This paper is concerned with the design problem of robust dynamic output feedback model predictive controllers for a class of discrete-time systems with time-varying network-induced delays and nonlinear perturbation. The designed controllers achieve on-line suboptimal receding horizon guaranteed cost such that the system can be stabilized for all admissible uncertainties. A novel delay compensation strategy is proposed to eliminate the effects of the time-varying network-induced delays. By using multistep prediction and the receding optimization, the delay-dependent sufficient condition is derived for the existence of delay compensation controllers. By employing the cone complementarity linearization (CCL) idea, a nonlinear minimization problem with linear matrix inequality (LMI) constraints is formulated to design the desired output feedback controllers, and an iterative algorithm involving convex optimization is presented to solve the nonlinear minimization problem. Finally, an example is given to illustrate the feasibility and effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

This paper considers the stability and H∞ control problem of networked control systems with time delay. Taking into account the influence of network with delay, unknown input disturbance, and uncertainties of the system modeling, meanwhile we establish a precise, closed-loop model for networked control systems with time delay. By selecting a proper Lyapunov-Krasovskii function and using Lyapunov theorem, a sufficient condition for stability of the system in the form of LMI is demonstrated, corresponding controller parameters are acquired, and the convergence of the control algorithm is proved. The simulation example shows that the construction of the network robust control system with time delay indeed improves the stability performance of the system, which indicates the effectiveness of the design. [ABSTRACT FROM AUTHOR]

We present a new adaptive gain robust controller for polytopic uncertain systems. The proposed adaptive gain robust controller consists of a state feedback law with a fixed gain and a compensation input with adaptive gains which are tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed adaptive gain robust controller are given in terms of LMIs. Finally, illustrative examples are presented to show the effectiveness of the proposed adaptive gain robust controller. [ABSTRACT FROM AUTHOR]

We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA) is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule. [ABSTRACT FROM AUTHOR]

This paper addresses the exponential synchronization problem of a class of master-slave distributed parameter systems (DPSs) with spatially variable coefficients and spatiotemporally variable nonlinear perturbation, modeled by a couple of semilinear parabolic partial differential equations (PDEs). With a locally Lipschitz constraint, the perturbation is a continuous function of time, space, and system state. Firstly, a sufficient condition for the robust exponential synchronization of the unforced semilinear master-slave PDE systems is investigated for all admissible nonlinear perturbations. Secondly, a robust distributed proportional-spatial derivative (P-sD) state feedback controller is desired such that the closed-loop master-slave PDE systems achieve exponential synchronization. Using Lyapunov’s direct method and the technique of integration by parts, the main results of this paper are presented in terms of spatial differential linear matrix inequalities (SDLMIs). Finally, two numerical examples are provided to show the effectiveness of the proposed methods applied to the robust exponential synchronization problem of master-slave PDE systems with nonlinear perturbation. [ABSTRACT FROM AUTHOR]

With the advantages such as high security and far responding distance, the passive location has a broad application in military and civil domains such as radar and aerospace. However, most of the current passive location methods are based on the framework of the probability theory and cannot be used to deal with fuzzy uncertainty in the passive location systems. Though the fuzzy Kalman filter can be used in the uncertainty systems, it could not deal with the abrupt change of state like the maneuvering target which will lead to the filter divergence. Therefore, in order to track the maneuvering target in the fuzzy passive system, we proposed a robust fuzzy extended Kalman filter based on the orthogonality principle and the fuzzy filter in the paper. Conclusion can be made based on the simulation result that this new approach is more precise and more robust than the fuzzy filter. [ABSTRACT FROM AUTHOR]

This paper presents a pulse shaping method robust to insufficient synchronization in orthogonal frequency division multiplexing with offset quadrature amplitude modulation (OFDM/OQAM) systems over doubly dispersive (DD) channels. The proposed pulse is designed as a linear combination of several well localized Hermite functions. The coefficients optimization problem is modeled as a nonconvex constrained fractional programming problem based on the signal-to-interference ratio (SIR) maximization criterion. An efficient iterative algorithm is applied to simplify the problem to a series of quadratically constrained quadratic program (QCQP) problems which can be solved by semidefinite relaxation (SDR) method. Simulation results show that the proposed pulse is superior to traditional pulses with respect to SIR performance over DD channels in the presence of carrier frequency offset (CFO) and timing offset (TO). [ABSTRACT FROM AUTHOR]

This paper deals with the discrete event-triggered robust fault-tolerant control problem for uncertain nonlinear networked control systems (NNCSs) with α-safety degree. A discrete event-triggered communication scheme (DETCS) is initially proposed, and a closed-loop fault model is subsequently established for NNCSs with actuator saturation under the DETCS. Based on an appropriately constructed delay-dependent Lyapunov–Krasovskii function, sufficient conditions are derived to guarantee the asymptotic stability of NNCSs under two different event-triggered conditions and are established as the contractively invariant sets of fault tolerance with α-safety degree. Furthermore, codesign methods between the robust fault-tolerant controller and event-triggered weight matrix are also proposed in terms of linear matrix inequality. The simulation shows that the resultant closed-loop fault NNCSs possesses a high safety margin, and an improved dynamic performance, as well as a reduced communication load. A comparative analysis of the two event-triggered conditions is discussed in the experiment section. [ABSTRACT FROM AUTHOR]

The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias correcting forecasting method, which includes the combination forecasting method and forecasting bias correcting model. The forecasting result shows that the combination bias correcting forecasting method can more accurately forecast the trend of wind speed and has a good robustness. [ABSTRACT FROM AUTHOR]

Wireless sensor network consists of hundreds or thousands of low cost, low power, and self-organizing tiny sensor nodes that are deployed within the sensor network. Sensor network is susceptible to physical attacks due to deprived power and restricted resource capability and is exposed to external environment for transmitting and receiving data. Node capture attack is one of the most menacing attack in the wireless sensor network and may be physically captured by an adversary for extracting confidential information regarding cryptographic keys, node’s unique id, and so forth, from its memory to eliminate the confidentiality and integrity of the wireless links. Node capture attack suffers from severe security breach and tremendous network cost. We propose an empirically designed multiple objectives node capture attack algorithm based on optimization functions as an effective solution against the attacking efficiency of node capture attack. Finding robust assailant optimization-particle swarm optimization and genetic algorithm (FiRAO-PG) consists of multiple objectives: maximum node participation, maximum key participation, and minimum resource expenditure to find optimal nodes using PSO and GA. It will leverage a comprehensive tool to destroy maximum portion of the network realizing cost-effectiveness and higher attacking efficiency. The simulation results manifest that FiRAO-PG can provide higher fraction of compromised traffic than matrix algorithm (MA) so the attacking efficiency of FiRAO-PG is higher. [ABSTRACT FROM AUTHOR]

Multirotor helicopter attracts more attention due to its increased load capacity and being highly maneuverable. However, these helicopters are uncertain multivariable systems, which pose a challenge for their robust controller design. In this paper, a robust two-loop control scheme is proposed for a hexarotor system. The resulted controller consists of a nominal controller and a robust compensator. The robust compensators are added to restrain the influences of uncertainties such as nonlinear dynamics, coupling, parametric uncertainties, and external disturbances. It is proven that the tracking errors are ultimately bounded with specified boundaries by choosing the parameters of the robust compensators. Simulation results on the hexarotor demonstrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

The problem of robust H∞ filtering is investigated for discrete-time Markov jump linear system (DMJLS) with uncertain parameters and missing measurements. The missing measurements process is modelled as a Bernoulli distributed sequence. A robust H∞ filter is designed and sufficient conditions are established in terms of linear matrix inequalities via a mode-dependent Lyapunov function approach, such that, for all admissible uncertain parameters and missing measurements, the resulting filtering error system is robustly stochastically stable and a guaranteed H∞ performance constraint is achieved. Furthermore, the optimal H∞ performance index is subsequently obtained by solving a convex optimisation problem and the missing measurements effects on the H∞ performance are evaluated. A numerical example is given to illustrate the feasibility and effectiveness of the proposed filter. [ABSTRACT FROM AUTHOR]

Based on the traditional machine vision recognition technology and traditional artificial neural networks about body movement trajectory, this paper finds out the shortcomings of the traditional recognition technology. By combining the invariant moments of the three-dimensional motion history image (computed as the eigenvector of body movements) and the extreme learning machine (constructed as the classification artificial neural network of body movements), the paper applies the method to the machine vision of the body movement trajectory. In detail, the paper gives a detailed introduction about the algorithm and realization scheme of the body movement trajectory recognition based on the three-dimensional motion history image and the extreme learning machine. Finally, by comparing with the results of the recognition experiments, it attempts to verify that the method of body movement trajectory recognition technology based on the three-dimensional motion history image and extreme learning machine has a more accurate recognition rate and better robustness. [ABSTRACT FROM AUTHOR]

Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S) fuzzy augmented model (TSFAM) as well as a TSFAM with uncertainty (TSFAMwU) is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1) a T-S fuzzy servo controller (TSFSC) designed from the TSFAM; (2) a robust TSFSC (RTSFSC) designed from the TSFAMwU; and (3) a robust T-S fuzzy dynamic regulator (RTSFDR) designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR. [ABSTRACT FROM AUTHOR]

This paper presents a new robust and efficient time integration algorithm suitable for various complex nonlinear structural dynamic finite element problems. Based on the idea of composition, the three-point backward difference formula and a generalized central difference formula are combined to constitute the implicit algorithm. Theoretical analysis indicates that the composite algorithm is a single-solver algorithm with satisfactory accuracy, unconditional stability, and second-order convergence rate. Moreover, without any additional parameters, the composite algorithm maintains a symmetric effective stiffness matrix and the computational cost is the same as that of the trapezoidal rule. And more merits of the proposed algorithm are revealed through several representative finite element examples by comparing with analytical solutions or solutions provided by other numerical techniques. Results show that not only the linear stiff problem but also the nonlinear problems involving nonlinearities of geometry, contact, and material can be solved efficiently and successfully by this composite algorithm. Thus the prospect of its implementation in existing finite element codes can be foreseen. [ABSTRACT FROM AUTHOR]

This paper presents a highly robust trajectory tracking controller for small unmanned helicopter with model uncertainties and external disturbances. First, a simplified dynamic model is developed, where the model uncertainties and external disturbances are treated as compounded disturbances. Then the system is divided into three interconnected subsystems: altitude subsystem, yaw subsystem, and horizontal subsystem. Second, a disturbance observer based controller (DOBC) is designed based upon backstepping and multivariable super twisting control algorithm to obtain robust trajectory tracking property. A sliding mode observer works as an estimator of the compounded disturbances. In order to lessen calculative burden, a first-order exact differentiator is employed to estimate the time derivative of the virtual control. Moreover, proof of the stability of the closed-loop system based on Lyapunov method is given. Finally, simulation results are presented to illustrate the effectiveness and robustness of the proposed flight control scheme. [ABSTRACT FROM AUTHOR]

The design of a robust fault estimation observer is studied for linear multiagent systems subject to incipient faults. By considering the fact that incipient faults are in low-frequency domain, the fault estimation of such faults is proposed for discrete-time multiagent systems based on finite-frequency technique. Moreover, using the decomposition design, an equivalent conclusion is given. Simulation results of a numerical example are presented to demonstrate the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

This paper presents a controller for a class of robotic systems, based on a first-order sliding mode with a particular noninvariant, nonconnected surface. With this control it is possible to regulate the position such that the velocity remains, as long as possible, at a specified value until the system is close to the desired position. The properties inherited from the sliding modes make the control exhibit a high robustness to external perturbations and low sensitivity to system parameter variations. It is shown that the desired speed is reached in a finite time and the system converges exponentially to the desired position. This controller can be applied to systems described by a classical model of a fully actuated, n-DOF mechanical system, which could be decoupled via a preliminary decoupling control. To illustrate the theoretical results, the proposed control technique is applied to a Cartesian robot, simulated numerically. Moreover, to show the effectiveness of this strategy, some physical experiments on a rotational (mechanical) device were performed. [ABSTRACT FROM AUTHOR]

This paper deals with the hierarchical laminated shell elements with nonsensitivity to adverse conditions for linear static analysis of cylindrical problems. Displacement approximation of the elements is established by high-order shape functions using the integrals of Legendre polynomials to ensure C0 continuity at the interface between adjacent elements. For exact linear mapping of cylindrical shell problems, cylindrical coordinate is adopted. To find global response of laminated composite shells, equivalent single-layer theory is also considered. Thus, the proposed elements are formulated by the dimensional reduction from three-dimensional solid to two-dimensional plane which allows the first-order shear deformation and considers anisotropy due to fiber orientation. The sensitivity tests are implemented to show robustness of the present elements with respect to severe element distortions, very high aspect ratios of elements, and very large radius-to-thickness ratios of shells. In addition, this element has investigated whether material conditions such as isotropic and orthotropic properties may affect the accuracy as the element distortion ratio is increased. The robustness of present element has been compared with that of several shell elements available in ANSYS program. [ABSTRACT FROM AUTHOR]

This paper describes an original technique for the joint feature and model selection in the context of support vector machine (SVM) classification applied as a diagnosis strategy in model-based fault detection and isolation (FDI). We demonstrate that the proposed technique contributes to the solution of an open research problem: to design a robust FDI procedure, correctly functioning with different operating conditions and fault sizes, specifically settled for an electric generation system based on solid oxide fuel cells (SOFCs). By using a quantitative model of the generation system coupled to an optimized SVM classifier, a satisfactory FDI procedure is achieved, which is robust against modeling and measurement errors and is compliant with practical deployment. [ABSTRACT FROM AUTHOR]

By using the quasi-conforming element technique, two four-node quadrilateral membrane elements with 2 degrees of freedom at each node (Q4-like membrane element) are formulated in rectangular Cartesian coordinates. One of the four-node quadrilateral membrane elements is based on the assumed strain field with only five independent strain parameters and accounting for the Poisson effect explicitly. There are no independent internal parameters and numerical integration involved in the evaluation of the strain parameters in these four-node quadrilateral membrane elements, and their element stiffness matrices are computed explicitly in Cartesian coordinates. Consequently, the formulation of these four-node quadrilateral membrane elements is extremely simple, and the resulting elements are very computationally efficient. These two quasi-conforming quadrilateral membrane elements pass the patch test and are free from shear locking and insensitive to the element distortion in the range of practical application. The numerical result comparison with other four-node quadrilateral membrane elements, including Q4-like plane elements with drilling degrees of freedom and the Q6-type isoparametric elements with very complicated nonconforming modes, shows that the present quasi-conforming quadrilateral membrane elements are not only reliable and robust, but also very accurate in both displacement and stress evaluations in the analysis of practical plane elasticity problems. [ABSTRACT FROM AUTHOR]

The longitudinal nonlinear aircraft model with cargo extraction is derived using theoretical mechanics and flight mechanics. Furthermore, the nonlinear model is approximated by a semilinear time-varying system with the cargo disturbances viewed as unknown nonlinearities, both matched and unmatched types. On this basis, a novel autopilot inner-loop based on the LQR and L1 adaptive theory is developed to reject the unknown nonlinear disturbances caused by the cargo and also to accommodate uncertainties. Analysis shows that the controller can guarantee robustness in the presence of fast adaptation, without exciting control signal oscillations and gain scheduling. The overall control system is completed with the outer-loop altitude-hold control based on a PID controller. Simulations are conducted under the condition that one transport aircraft performs maximum load airdrop mission at the height of 82 ft, using single row single platform mode. The results show the good performance of the control scheme, which can meet the airdrop mission performance indexes well, even in the presence of ±20% aerodynamic uncertainties. [ABSTRACT FROM AUTHOR]

With more color images being widely used on the Internet, the research on embedding color watermark image into color host image has been receiving more attention. Recently, Su et al. have proposed a robust and blind watermarking scheme for dual color image, in which the main innovation is the using of two-level DCT. However, it has been demonstrated in this paper that the original scheme in Su’s study is not secure and can be attacked by our proposed method. In addition, some errors in the original scheme have been pointed out. Also, an improvement measure is presented to enhance the security of the original watermarking scheme. The proposed method has been confirmed by both theoretical analysis and experimental results. [ABSTRACT FROM AUTHOR]

In dynamic multiobjective optimization problems, the environmental parameters change over time, which makes the true pareto fronts shifted. So far, most works of research on dynamic multiobjective optimization methods have concentrated on detecting the changed environment and triggering the population based optimization methods so as to track the moving pareto fronts over time. Yet, in many real-world applications, it is not necessary to find the optimal nondominant solutions in each dynamic environment. To solve this weakness, a novel method called robust pareto-optimal solution over time is proposed. It is in fact to replace the optimal pareto front at each time-varying moment with the series of robust pareto-optimal solutions. This means that each robust solution can fit for more than one time-varying moment. Two metrics, including the average survival time and average robust generational distance, are present to measure the robustness of the robust pareto solution set. Another contribution is to construct the algorithm framework searching for robust pareto-optimal solutions over time based on the survival time. Experimental results indicate that this definition is a more practical and time-saving method of addressing dynamic multiobjective optimization problems changing over time. [ABSTRACT FROM AUTHOR]

The sliding mode control (SMC) technique with a first-order low-pass filter (LPF) is incorporated with a new adaptive PID controller. It is proposed for tracking control of an uncertain nonlinear system. In the proposed control scheme, the adaptation law is able to update the PID controller online during the control process within a short period. The chattering phenomenon of the SMC can be alleviated by incorporation of a first-order LPF, while the robustness of the control system is similar to that of the sliding mode. In the closed-loop control analysis, the convergence condition in the reaching phase and the existence condition of the sliding mode were analyzed. The stability of the closed-loop control is guaranteed in the sense of Lyapunov’s direct method. The simulations and experimental applications of a speed tracking control of a spark ignition (SI) engine via electronic throttle valve control architecture are provided to verify the effectiveness and the feasibility of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The session initiation protocol (SIP) is a powerful application-layer protocol which is used as a signaling one for establishing, modifying, and terminating sessions among participants. Authentication is becoming an increasingly crucial issue when a user asks to access SIP services. Hitherto, many authentication schemes have been proposed to enhance the security of SIP. In 2014, Arshad and Nikooghadam proposed an enhanced authentication and key agreement scheme for SIP and claimed that their scheme could withstand various attacks. However, in this paper, we show that Arshad and Nikooghadam’s authentication scheme is still susceptible to key-compromise impersonation and trace attacks and does not provide proper mutual authentication. To conquer the flaws, we propose a secure and efficient ECC-based authentication scheme for SIP. Through the informal and formal security analyses, we demonstrate that our scheme is resilient to possible known attacks including the attacks found in Arshad et al.’s scheme. In addition, the performance analysis shows that our scheme has similar or better efficiency in comparison with other existing ECC-based authentication schemes for SIP. [ABSTRACT FROM AUTHOR]

Water distribution network is important in the critical physical infrastructure systems. The paper studies the emergency resource strategies on water distribution network with the approach of complex network and cascading failures. The model of cascade-based emergency for water distribution network is built. The cascade-based model considers the network topology analysis and hydraulic analysis to provide a more realistic result. A load redistribution function with emergency recovery mechanisms is established. From the aspects of uniform distribution, node betweenness, and node pressure, six recovery strategies are given to reflect the network topology and the failure information, respectively. The recovery strategies are evaluated with the complex network indicators to describe the failure scale and failure velocity. The proposed method is applied by an illustrative example. The results showed that the recovery strategy considering the node pressure can enhance the network robustness effectively. Besides, this strategy can reduce the failure nodes and generate the least failure nodes per time. [ABSTRACT FROM AUTHOR]

Although the original particle swarm optimizer (PSO) method and its related variant methods show some effectiveness for solving optimization problems, it may easily get trapped into local optimum especially when solving complex multimodal problems. Aiming to solve this issue, this paper puts forward a novel method called parallel and cooperative particle swarm optimizer (PCPSO). In case that the interacting of the elements in D-dimensional function vector X=[x1,x2,…,xd,…,xD] is independent, cooperative particle swarm optimizer (CPSO) is used. Based on this, the PCPSO is presented to solve real problems. Since the dimension cannot be split into several lower dimensional search spaces in real problems because of the interacting of the elements, PCPSO exploits the cooperation of two parallel CPSO algorithms by orthogonal experimental design (OED) learning. Firstly, the CPSO algorithm is used to generate two locally optimal vectors separately; then the OED is used to learn the merits of these two vectors and creates a better combination of them to generate further search. Experimental studies on a set of test functions show that PCPSO exhibits better robustness and converges much closer to the global optimum than several other peer algorithms. [ABSTRACT FROM AUTHOR]

We formulated a solution procedure for vehicle routing problems with uncertainty (VRPU for short) with regard to future demand and transportation cost. Unlike E-SDROA (expectation semideviation robust optimisation approach) for solving the proposed problem, the formulation focuses on robust optimisation considering situations possibly related to bidding and capital budgets. Besides, numerical experiments showed significant increments in the robustness of the solutions without much loss in solution quality. The differences and similarities of the robust optimisation model and existing robust optimisation approaches were also compared. [ABSTRACT FROM AUTHOR]

The finite-time H∞ control problem is addressed for uncertain time-varying descriptor system with finite jumps and time-varying norm-bounded disturbance. Firstly, a sufficient condition of finite-time boundedness for the abovementioned class of system is obtained. Then the result is extended to finite-time H∞ for the system. Based on the condition, state feedback controller is designed such that the closed-loop system is finite-time boundedness and satisfies L2 gain. The conditions are given in terms of differential linear matrix inequalities (DLMIs) and linear matrix inequalities (LMIs), and such conditions require the solution of a feasibility problem involving DLMIs and LMIs, which can be solved by using existing linear algorithms. Finally, a numerical example is given to illustrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The problem of robust fault detection filter (FDF) design and optimization is investigated for a class of networked control systems (NCSs) with random delays. The NCSs are modeled as Markovian jump systems (MJSs) by assuming that the random delays obey a Markov chain. Based on the model, an observer-based residual generator is constructed and the corresponding fault detection problem is formulated as an H∞ filtering problem by which the error between the residual signal and the fault is made as small as possible. A sufficient condition for the existence of the desired FDF is derived in terms of linear matrix inequalities (LMIs). Furthermore, to improve the performance of the robust fault detection systems, a time domain optimization approach is proposed. The solution of the optimization problem is given in the form of Moore-Penrose inverse of matrix. A numerical example is provided to illustrate the effectiveness and potential of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO) method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the input time-delay existing in most thrust systems of the ships, the robust H∞ controller is designed for the ship dynamic positioning (DP) system with time-delay. The input delay system is turned to a neutral time-delay system by a state-derivative control law. The less conservative result is derived for the neutral system with state-derivative feedback by the delay-decomposition approach and linear matrix inequality (LMI). Finally, the numerical simulations demonstrate the asymptotic stability and robustness of the controller and verify that the designed DP controller is effective in the varying environment disturbances of wind, waves, and ocean currents. [ABSTRACT FROM AUTHOR]

Service-dominant (S-D) logic is a service science framework that is more robust than the traditional goods-dominant (G-D) logic. It emphasizes the importance of operant resources and value Cocreation. This study employs social cognitive theory to explore the triple reciprocity of organizational value Cocreation behavior. Further, this study uses DEMATEL-based ANP to examine the dynamic nature of organizational value Cocreation behavior. The major results of this study can be described as follows. First, the triadic reciprocity of personal, environmental, and behavioral factors are validated. Second, the dominant influencing trends are clearly identified. From a dimensional point of view, environmental factors affect personal factors and behavioral factors, and personal factors affect behavioral factors. Similarly, in terms of organizational value Cocreation behavior, organizational identification affects altruistic behavior and knowledge-sharing behavior, and altruistic behavior affects knowledge-sharing behavior. These findings may provide helpful guidance in effectively promoting organizational value cocreation behavior, enabling organizations to leverage operant resources to their maximum potential. [ABSTRACT FROM AUTHOR]

The problem of robust asymptotic stabilization is considered for a class of discrete-time uncertain linear systems with multiple uncertain time-delayed states and input constraints. Compared with other works in the literature, the proposed approach takes the information of the delayed states with the estimated time-delays indices into full consideration. Based on the predictive control principle of receding horizon optimization and Lyapunov stability theory combined with linear matrix inequalities (LMIs) techniques, a time-delayed state dependent quadratic function is considered for incorporating MPC problem formulation. The robust MPC problem is formulated to minimize the upper bound of infinite horizon cost that satisfies the sufficient conditions. The proposed approach allows for the synthesis of robust memory state feedback controllers with respect to uncertainties on the implemented delay. Since developing the improved memory state feedback controller, the novel improved method is much less conservative and more general. Finally, the numerical simulation results prove availability of the proposed method. [ABSTRACT FROM AUTHOR]

Frequency diversity is used to reduce the effect of destructive fading, so as to improve the communication quality, by passing the information symbols through multiple independently faded paths, and ensure that reliable communication is possible as long as one of these paths is strong. In this paper a multiorder orthogonal frequency division multiplexing (OFDM) frequency diversity approach using properties of order theory and Hamming distance is proposed. The frequency diversity is obtained by specifying proper correlations among the transmitted symbols. As subchannels experience independent fading, at least one of the symbols may have robust signal, which can be used by the receiver to detect other symbols. Considering bit error rate (BER) performance, power consumption, bandwidth utilization, and practical implementation expense, simulation results show that the proposed approach outperforms other OFDM diversity techniques, such as Maximal Ratio Combination (MRC) and Space Frequency Block Coding (SFBC). [ABSTRACT FROM AUTHOR]

This paper considers the problem of delay-dependent state estimation for neural networks with time-varying delays and stochastic parameter uncertainties. It is assumed that the parameter uncertainties are affected by the environment which is changed with randomly real situation, and its stochastic information such as mean and variance is utilized in the proposed method. By constructing a newly augmented Lyapunov-Krasovskii functional, a designing method of estimator for neural networks is introduced with the framework of linear matrix inequalities (LMIs) and a neural networks model with stochastic parameter uncertainties which have not been introduced yet. Two numerical examples are given to show the improvements over the existing ones and the effectiveness of the proposed idea. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of robust generalized H2 filter design for uncertain discrete-time fuzzy systems with output quantization. Firstly, the outputs of the system are quantized by a memoryless logarithmic quantizer before being transmitted to a filter. Then, attention is focused on the design of a generalized H2 filter to mitigate quantization effects, such that the filtering error systems ensure the robust stability with a prescribed generalized H2 noise attenuation level. Via applying Finsler lemma to introduce some slack variables and using the fuzzy Lyapunov function, sufficient conditions for the existence of a robust generalized H2 filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Head pose estimation from single 2D images has been considered as an important and challenging research task in computer vision. This paper presents a novel head pose estimation method which utilizes the shape model of the Basel face model and five fiducial points in faces. It adjusts shape deformation according to Laplace distribution to afford the shape variation across different persons. A new matching method based on PSO (particle swarm optimization) algorithm is applied both to reduce the time cost of shape reconstruction and to achieve higher accuracy than traditional optimization methods. In order to objectively evaluate accuracy, we proposed a new way to compute the pose estimation errors. Experiments on the BFM-synthetic database, the BU-3DFE database, the CUbiC FacePix database, the CMU PIE face database, and the CAS-PEAL-R1 database show that the proposed method is robust, accurate, and computationally efficient. [ABSTRACT FROM AUTHOR]

This paper studies the robust adaptive fuzzy control design problem for a class of uncertain multiple-input and multiple-output (MIMO) nonlinear systems in the presence of actuator amplitude and rate saturation. In the control scheme, fuzzy logic systems are used to approximate unknown nonlinear systems. To compensate the effect of input saturations, an auxiliary system is constructed and the actuator saturations then can be augmented into the controller. The modified tracking error is introduced and used in fuzzy parameter update laws. Furthermore, in order to deal with fuzzy approximation errors for unknown nonlinear systems and external disturbances, a robust compensation control is designed. It is proved that the closed-loop system obtains H∞ tracking performance through Lyapunov analysis. Steady and transient modified tracking errors are analyzed and the bound of modified tracking errors can be adjusted by tuning certain design parameters. The proposed control scheme is applicable to uncertain nonlinear systems not only with actuator amplitude saturation, but also with actuator amplitude and rate saturation. Detailed simulation results of a rigid body satellite attitude control system in the presence of parametric uncertainties, external disturbances, and control input constraints have been presented to illustrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This study focuses on the design of the robust fault-tolerant control (FTC) system based on adaptive observer for uncertain linear time invariant (LTI) systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA) using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI) technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods. [ABSTRACT FROM AUTHOR]

The paper concerns the problem of stabilization of large-scale fractional order uncertain systems with a commensurate order 1<α<2 under controller gain uncertainties. The uncertainties are of norm-bounded type. Based on the stability criterion of fractional order system, sufficient conditions on the decentralized stabilization of fractional order large-scale uncertain systems in both cases of additive and multiplicative gain perturbations are established by using the complex Lyapunov inequality. Moreover, the decentralized nonfragile controllers are designed. Finally, some numerical examples are given to validate the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the problems of robust stabilization and disturbance rejection for a class of positive systems with time-varying delays and actuator saturation. First, a convex hull representation is used to describe the saturation characteristics. By constructing an appropriate copositive type Lyapunov functional, we give sufficient conditions for the existence of a state feedback controller such that the closed-loop system is positive and asymptotically stable at the origin of the state space with a domain of attraction. Then, the disturbance rejection performance analysis in the presence of actuator saturation is developed via L1-gain. The design method is also extended to investigate the problem of L1-gain analysis for uncertain positive systems with time-varying delays and actuator saturation. Finally, three examples are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A novel variable structure compensation PID control, VSCPID in short, is proposed for trajectory tracking of asymmetrical hydraulic cylinder systems. This new control method improves the system robustness by adding a variable structure compensation term to the conventional PID control. The variable structure term is designed according to sliding mode control method and therefore could compensate the disturbance and uncertainty. Meanwhile, the proposed control method avoids the requirements for exact knowledge of the systems associated with equivalent control value in SMC that means the controller is simple and easy to design. The stability analysis of this approach is conducted with Lyapunov function, and the global stability condition applied to choose control parameters is provided. Simulation results show the VSCPID control can achieve good tracking performances and high robustness compared with the other control methods under the uncertainties and varying load conditions. [ABSTRACT FROM AUTHOR]

We propose a predictive sliding mode control (PSMC) scheme for attitude control of hypersonic vehicle (HV) with system uncertainties and external disturbances based on an improved fuzzy disturbance observer (IFDO). First, for a class of uncertain affine nonlinear systems with system uncertainties and external disturbances, we propose a predictive sliding mode control based on fuzzy disturbance observer (FDO-PSMC), which is used to estimate the composite disturbances containing system uncertainties and external disturbances. Afterward, to enhance the composite disturbances rejection performance, an improved FDO-PSMC (IFDO-PSMC) is proposed by incorporating a hyperbolic tangent function with FDO to compensate for the approximate error of FDO. Finally, considering the actuator dynamics, the proposed IFDO-PSMC is applied to attitude control system design for HV to track the guidance commands with high precision and strong robustness. Simulation results demonstrate the effectiveness and robustness of the proposed attitude control scheme. [ABSTRACT FROM AUTHOR]

We propose a new method for the motion segmentation using a moving camera. The proposed method classifies each image pixel in the image sequence as the background or the motion regions by applying a novel three-view constraint called the “parallax-based multiplanar constraint.” This new three-view constraint, being the main contribution of this paper, is derived from the relative projective structure of two points in three different views and implemented within the “Plane + Parallax” framework. The parallax-based multiplanar constraint overcomes the problem of the previous geometry constraint and does not require the reference plane to be constant across multiple views. Unlike the epipolar constraint, the parallax-based multiplanar constraint modifies the surface degradation to the line degradation to detect the motion objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the parallax-based multiplanar constraint. [ABSTRACT FROM AUTHOR]

Edge detection is a fundamental task in many computer vision applications. In this paper, we propose a novel multiscale edge detection approach based on the nonsubsampled contourlet transform (NSCT): a fully shift-invariant, multiscale, and multidirection transform. Indeed, unlike traditional wavelets, contourlets have the ability to fully capture directional and other geometrical features for images with edges. Firstly, compute the NSCT of the input image. Secondly, the K-means clustering algorithm is applied to each level of the NSCT for distinguishing noises from edges. Thirdly, we select the edge point candidates of the input image by identifying the NSCT modulus maximum at each scale. Finally, the edge tracking algorithm from coarser to finer is proposed to improve robustness against spurious responses and accuracy in the location of the edges. Experimental results show that the proposed method achieves better edge detection performance compared with the typical methods. Furthermore, the proposed method also works well for noisy images. [ABSTRACT FROM AUTHOR]