Search

For synchronization of a class of chaotic systems in the presence of nonvanishing uncertainties, a novel time-varying gain observer-based sliding mode control is proposed. First, a novel time-varying gain disturbance observer (TVGDO) is developed to estimate the uncertainties. Then, by using the output of TVGDO to modify sliding mode control (SMC), a new TVGDO-based SMC scheme is developed. Although the observation and control precision of conventional fixed gain disturbance observer-based control (FGDOC) for chaotic systems can be guaranteed by a high observer gain, the undesirable spike problem may be caused by the high gain if the initial values of estimate and true states are not equal. The most attractive feature of this work is that the newly proposed TVGDO can eliminate the spike problem by developing a time-varying gain scheme. Finally, the effectiveness of the proposed method is demonstrated by the numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, chaotic synchronization with uncertainties and disturbances is studied. Firstly, a new control method based on UDE control is proposed, which is composed of two controllers: one is the stabilization controller in order to realize the stabilization of nominal system without uncertainties and disturbances and the other is the UDE controller in order to deal with the given controlled system with both uncertainties and disturbances. Then, two examples are studied by the above method. Finally, the correctness and effectiveness of the method are verified by numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, a 3D jerk chaotic system with hidden attractor was explored, and the dissipativity, equilibrium, and stability of this system were investigated. The attractor types, Lyapunov exponents, and Poincare section of the system under different parameters were analyzed. Additionally, a circuit was carried out, and a good similarity between the circuit experimental results and the theoretical analysis testifies the feasibility and practicality of the original system. Furthermore, a robust feedback controller was designed based on the finite-time stability theory, which guarantees the synchronization of 3D jerk master-slave system in finite time and asymptotically converges to the origin. Finally, we also give verification for the discussion in this paper by numerical simulation. [ABSTRACT FROM AUTHOR]

In this study, a control scheme that allows performing height position regulation and stabilization for an unmanned planar vertical take-off and landing aerial vehicle, in the presence of disturbance due to wind, is presented. To this end, the backstepping procedure together with nested saturation function method is used. Firstly, a convenient change of coordinates in the aerial vehicle model is carried out to dissociate the rotational dynamics from the translational one. Secondly, the backstepping procedure is applied to obtain the height position controller, allowing the reduction of the system and expressing it as an integrator chain with nonlinear disturbance. Therefore, the nested saturation function method is used to obtain a stabilizing controller for the horizontal position and roll angle. The corresponding stability analysis is conducted via the Lyapunov second method. In addition, to estimate the disturbance due to wind, an extended state observer is used. The effectiveness of the proposed control scheme is assessed through numerical simulations, from which convincing results have been obtained. [ABSTRACT FROM AUTHOR]

This paper focuses on the robust control of fractional-order economical chaotic system (FOECS) with parametric uncertainties and external disturbances. The dynamical behavior of FOECS is studied by numerical simulation, and circuit implementations of FOECS are also given. Based on fractional-order Lyapunov stability theorems, a robust adaptive controller, which can guarantee that all signals remain bounded and the tracking error tends to a small region, is designed. The proposed method can be used to control a large range of fractional-order systems with system uncertainties. Fractional-order adaptation laws are constructed to update the estimation of adaptive parameters. Finally, the robustness and effectiveness of our control method are indicated by simulation results. [ABSTRACT FROM AUTHOR]

To achieve fast and accurate adjustment of robotic fish, this paper proposes state prediction model based on the extreme learning machine optimized by particle swarm algorithm. The proposed model can select desirable actions for robotic fish according to precisely predicted states, "adjusting position" or "pushing ball" defined herein. Specifically, the extreme learning machine (ELM) is leveraged to predict the state of robotic fish, from the observations of current surrounding environment. As the outputs in ELM are varying with the randomly initialized parameters, particle swarm optimization (PSO) algorithm further improves the accuracy and robustness of the ELM by optimizing initial parameters. The empirical results on URWPGSim2D simulation platform indicate that the robotic fish tends to carry out appropriate actions using the state prediction model so that we can complete the game efficiently. It proves that the proposed model can make best use of the real-time information of robotic fish and water polo and derive fulfilling action strategy in various scenarios, which meet the requirements of motion control for robotic fish. [ABSTRACT FROM AUTHOR]

For the future information confrontation, a single jamming mode is not effective due to the complex electromagnetic environment. Selecting the appropriate jamming decision to coordinately allocate the jamming resources is the development direction of the electronic countermeasures. Most of the existing studies about jamming decision only pay attention to the jamming benefits, while ignoring the jamming cost. In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. Against the issue, this paper introduces the concept of jamming cost in the cognitive collaborative jamming decision model and refines it as a multiobjective one. Furthermore, this paper proposes a tabu search-artificial bee colony (TSABC) algorithm to cognitive cooperative-jamming decision. It introduces the tabu list into the artificial bee colony (ABC) algorithm and stores the solution that has not been updated after a certain number of searches into the tabu list to avoid meeting them when generating a new solution, so that this algorithm reduces the unnecessary iterative process, and it is not easy to fall into a local optimum. Simulation results show that the search ability and probability of finding the optimal solution of the new algorithm are better than the other two. It has better robustness, which is better in the "one-to-many" jamming mode. [ABSTRACT FROM AUTHOR]

In this paper, the problem of robust preview control for uncertain discrete singular systems is considered. First of all, by employing the forward difference for uncertain discrete singular systems, the singular augmented error system with the state vector, the input control vector, and the previewable reference signal is derived. Since there is a singular matrix in the system, the existing method cannot be directly applied to this problem. By considering the stability of the transposition system with Linear Matrix Inequality (LMI) method, a new stability criterion for the transposition system is introduced. Then, the robust controller for the augmented error system is obtained, which is regarded as the robust preview controller for the original singular system. At last, the numerical simulation shows the correctness and effectiveness of the results. [ABSTRACT FROM AUTHOR]

Summary: Cleaner energy production system such as direct alcohol fuel cells (DAFCs) are considered as an alternative source for generating cleaner energy. Studies based on design of catalysts, electrodes design, proton exchange membrane, and flow field were conducted for improving its performance characteristic such as power density. However, the less focus was paid on determining the operating conditions considering the uncertainties that will result in an increase of power density of DAFCs. Therefore, the present work proposes a novel comprehensive procedure involving experimental study and evolutionary approach of genetic programming (GP) in formulation of robust power density models for DAFCs. Two uncertainties such as the selection of objective function and variations in measurement of operating conditions are incorporated in framework of GP. The power density models incorporate the formulation of new objective function in GP that will result in higher accuracy of the models. Experiments performed on DAFCs validate performance of the models. Simulation profiler is then generated for models to verify its robustness in uncertain operating conditions. The inferences on relationships between power density and operating conditions for DAFCs are made by surface analysis of the models. [ABSTRACT FROM AUTHOR]

As a novel swarm intelligence algorithm, artificial bee colony (ABC) algorithm inspired by individual division of labor and information exchange during the process of honey collection has advantage of simple structure, less control parameters, and excellent performance characteristics and can be applied to neural network, parameter optimization, and so on. In order to further improve the exploration ability of ABC, an artificial bee colony algorithm with random location updating (RABC) is proposed in this paper, and the modified search equation takes a random location in swarm as a search center, which can expand the search range of new solution. In addition, the chaos is used to initialize the swarm population, and diversity of initial population is improved. Then, the tournament selection strategy is adopted to maintain the population diversity in the evolutionary process. Through the simulation experiment on a suite of unconstrained benchmark functions, the results show that the proposed algorithm not only has stronger exploration ability but also has better effect on convergence speed and optimization precision, and it can keep good robustness and validity with the increase of dimension. [ABSTRACT FROM AUTHOR]

We propose a strategy to solve the tracking and regulation problem for a 2DOF underactuated mass-spring-damper system with backlash on the underactuated joint, parametric uncertainties, and partial measurement of the state vector. The design of the controller is divided into two stages; in the first stage, it is assumed that the full state vector and all perturbations in the system are available. The model is divided into one actuated subsystem and one underactuated subsystem. The position of the actuated mass is defined as the control input of the underactuated subsystem, which is designed as an ideal controller that solves the tracking and regulation control problems for the underactuated mass. Finally, the control input of the actuated subsystem is designed to solve the tracking problem considering as a reference signal the control signal of the underactuated subsystem. The second stage solves the problem of the implementation of the previously designed ideal controller using the active disturbances rejection control structure (ADRC). Here state observers estimate the nonmeasured state variables and, at the same time, estimate perturbations and auxiliary signals for their compensation. The performance of the closed-loop system is illustrated by numerical simulations and experimental results. [ABSTRACT FROM AUTHOR]

The present work deals with the design problem of a robust observer-based controller for a motorcycle system using LPV approach. The designed model is specifically uncertain and disturbed one, whose uncertainties are related to variations of both the cornering stiffness and the longitudinal velocity. The nonlinear motorcycle model is firstly transformed on an uncertain LPV model with two vertices; then an observer-based H∞ robust controller is designed. Both the controller and observer gain matrices are computed by solving a unified convex optimization problem under LMI constraints using YALMIP solver. Numerical simulation results are given to illustrate the effectiveness of the designed method. [ABSTRACT FROM AUTHOR]

We consider the optimal design of a sequence of quantum barriers, in order to manufacture an electronic device at the nanoscale such that the dependence of its transmission coefficient on the bias voltage is linear. The technique presented here is easily adaptable to other response characteristics. There are two distinguishing features of our approach. First, the transmission coefficient is determined using a semiclassical approximation, so we can explicitly compute the gradient of the objective function. Second, in contrast with earlier treatments, manufacturing uncertainties are incorporated in the model through random variables; the optimal design problem is formulated in a probabilistic setting and then solved using a stochastic collocation method. As a measure of robustness, a weighted sum of the expectation and the variance of a least-squares performance metric is considered. Several simulations illustrate the proposed technique, which shows an improvement in accuracy over 69% with respect to brute-force, Monte-Carlo-based methods. [ABSTRACT FROM AUTHOR]

The sliding mode control (SMC) strategy is employed to a permanent magnet synchronous motor (PMSM) vector control system in this study to improve system robustness against parameter variations and load disturbance. To decrease the intrinsic chattering behavior of SMC, a speed SMC with an adaptive law and an extended state observer (ESO) is proposed. In this method, based on the Lyapunov stability theorem, adaptive estimation laws are deduced to estimate uncertainties of a PMSM caused by parameter variations and unmodeled dynamics. Online estimated uncertainties can be used to eliminate the effect caused by the real uncertainties. In addition, an ESO is applied to observe the load disturbance in real time. The load disturbance observed value is then utilized to the output side of the speed adaptive SMC controller as feed-forward compensation. Both the simulation and experiment results demonstrate that the proposed approach effectively alleviates system chattering and enhances system robustness against uncertainty and load disturbance. [ABSTRACT FROM AUTHOR]

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

Structural control systems based on wireless sensors offer a convenient, flexible and cost-effective alternative to their wired counterparts. Although wireless control systems (WCSs) have several attractive features, some challenges do remain related to the persistent presence of network-induced time delays, and potential for sensor data losses and in extreme cases, sensor failures. The consequences of these challenges should be investigated, and solutions should be developed to achieve highly effective and robust control systems. The availability of such solutions will also encourage the adoption of WCSs in real structures. Here, an estimator switching method intended to minimize the influence of potential faults is developed and validated for WCSs. In this method, the switching gains are pre-calculated to enable real-time implementation. The proposed method is verified through numerical simulations of a seismically excited, three-story structure considering various sensor data loss and sensor failure scenarios. The robustness of this estimation method in the presence of measurement noise and modeling uncertainty is also investigated. In addition, the estimation switching method is incorporated into a closed-loop WCS in experiment. The results demonstrate the effectiveness of the proposed state estimation method in mitigating the impact of sensor data loss and sensor failure. [ABSTRACT FROM AUTHOR]

We propose a robust wireless relay scheme in narrow-band communications for IoT access, which matches the typical features of IoT often carrying relatively low data rate with limited bandwidth. This framework is towards offering robustness in QoS guarantees with emphases on security and/or reliability, and we use the security-assured network as the typical scenario. In particular, we consider a dual-hop relay network including a transmitter, a receiver, an amplify-and-forward (AF) untrusted relay, and a jamming node. The jamming node is treated as a helper. Specifically, the jammer broadcasts artificial noise (AN), which in fact pollutes both the untrusted relay and the destination node’s signals. However, we show that such AN can be effectively mitigated after the destination node obtains the forwarded signal from the relay, while the untrusted relay node cannot do so. The core idea for robustness assurance is to exploit higher signal dimensions at the receiver over the untrusted relay node. Simulations and analyses are also conducted to demonstrate that our proposed scheme can make the performance at the untrusted relay an interference-limited manner while completely removing the interferences at the receiver, therefore corroborating our claim in robustness in terms of security and reliability. [ABSTRACT FROM AUTHOR]

In this paper an issue related to electric energy management on board an aircraft is considered. A battery pack is connected to a high-voltage bus through a controlled Battery Charge/Discharge Unit (BCDU) that makes the overall behaviour of the battery “intelligent.” Specifically, when the aeronautic generator feeding the high-voltage bus has enough energy the battery is kept under charge, while if more loads are connected to the bus, so that the overload capacity of the generator is exceeded, the battery “helps” the generator by releasing its stored energy. The core of the application is a robust, supervised control strategy for the BCDU that automatically reverts the flow of power in the battery, when needed. Robustness is guaranteed by a low-level high gain control strategy. Switching from full-charge mode (i.e., when the battery absorbs power from the generator) to generator mode (i.e., when the battery pumps energy on the high-voltage bus) is imposed by a high-level supervisor. Different from previous approaches, mathematical proofs of stability are given for the controlled system. A switching implementation using a finite-time convergent controller is also proposed. The effectiveness of the proposed strategy is shown by detailed simulations in Matlab/Stateflow/SimPowerSystem. [ABSTRACT FROM AUTHOR]

Dual-winding bearingless switched reluctance motor (BSRM) is a multivariable high-nonlinear system characterized by strong coupling, and it is not completely reversible. In this paper, a new decoupling control strategy based on improved inverse system method is proposed. Robust servo regulator is adopted for the decoupled plants to guarantee control performances and robustness. A phase dynamic compensation filter is also designed to improve system stability at high-speed. In order to explain the advantages of the proposed method, traditional methods are compared. The tracking and decoupling characteristics as well as disturbance rejection and robustness are deeply analyzed. Simulation and experiments results show that the decoupling control of dual-winding BSRM in both reversible and irreversible domains can be successfully resolved with the improved inverse system method. The stability and robustness problems induced by inverse controller can be effectively solved by introducing robust servo regulator and dynamic compensation filter. [ABSTRACT FROM AUTHOR]

This paper proposes multicriteria adaptive observers for a class of singular systems with unknown time-varying parameters. Two criteria for the H∞ disturbance attenuation level and the upper bound of an ultimate invariant set are scalarized into a single cost function and then it is minimized by varying the weight parameter, which creates the optimal trade-off curve or Pareto optimal points. The proposed multicriteria adaptive observers are shown to be able to easily include integral action for better robust performance. It is demonstrated with numerical simulations that the proposed multicriteria adaptive observers provide the good estimation accuracy and allow effective and compromising design by considering two different cost functions simultaneously. [ABSTRACT FROM AUTHOR]

One important mission of strategic defense is to develop an integrated layered Ballistic Missile Defense System (BMDS). Motivated by the queueing theory, we presented a work for the representation, modeling, performance simulation, and channels optimal allocation of the layered BMDS M/M/N queueing systems. Firstly, in order to simulate the process of defense and to study the Defense Effectiveness (DE), we modeled and simulated the M/M/N queueing system of layered BMDS. Specifically, we proposed the M/M/N/N and M/M/N/C queueing model for short defense depth and long defense depth, respectively; single target channel and multiple target channels were distinguished in each model. Secondly, we considered the problem of assigning limited target channels to incoming targets, we illustrated how to allocate channels for achieving the best DE, and we also proposed a novel and robust search algorithm for obtaining the minimum channel requirements across a set of neighborhoods. Simultaneously, we presented examples of optimal allocation problems under different constraints. Thirdly, several simulation examples verified the effectiveness of the proposed queueing models. This work may help to understand the rules of queueing process and to provide optimal configuration suggestions for defense decision-making. [ABSTRACT FROM AUTHOR]

This paper investigates the control performance of pounding tuned mass damper (PTMD) in reducing the dynamic responses of SDOF (Single Degree of Freedom) structure. Taking an offshore jacket-type platform as an example, the optimal damping ratio and the gap between mass block and viscoelastic material are presented depending on a parametric study. Control efficiency influenced by material properties and contact geometries for PTMD is analyzed here, as well as robustness of the device. The results of numerical simulations indicated that satisfactory vibration mitigation and robustness can be achieved by an optimally designed PTMD. Comparisons between PTMD and traditional TMD demonstrate the advantages of PTMD, not only in vibration suppression and costs but also in effective frequency bandwidth. [ABSTRACT FROM AUTHOR]

The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. Furthermore, the proposed method has good robustness which can process external random disturbances and uncertain parameters. Finally, the validity and superiority are proved by the numerical simulations. [ABSTRACT FROM AUTHOR]

Satellite remote sensing image target matching recognition exhibits poor robustness and accuracy because of the unfit feature extractor and large data quantity. To address this problem, we propose a new feature extraction algorithm for fast target matching recognition that comprises an improved feature from accelerated segment test (FAST) feature detector and a binary fast retina key point (FREAK) feature descriptor. To improve robustness, we extend the FAST feature detector by applying scale space theory and then transform the feature vector acquired by the FREAK descriptor from decimal into binary. We reduce the quantity of data in the computer and improve matching accuracy by using the binary space. Simulation test results show that our algorithm outperforms other relevant methods in terms of robustness and accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a new robust inverse optimal control strategy for flexible spacecraft attitude maneuvers in the presence of external disturbances and actuator constraint. A new constrained attitude controller for flexible spacecraft is designed based on the Sontag-type formula and a control Lyapunov function. This control law optimizes a meaningful cost functional and the stability of the resulting closed-loop system is ensured by the Lyapunov framework. A sliding mode disturbance observer is used to compensate unknown bounded external disturbances. The ultimate boundedness of estimation error dynamics is guaranteed via a rigorous Lyapunov analysis. Simulation results are provided to demonstrate the performance of the proposed control law. [ABSTRACT FROM AUTHOR]

Interval type-2 fuzzy logic controller (IT2FLC) method for controlling the speed with a direct stator flux orientation control of doubly fed induction motor (DFIM) is proposed. The fuzzy controllers have demonstrated their effectiveness in the control of nonlinear systems, and in many cases it is proved that their robustness and performance are less sensitive to parameters variation over conventional controllers. The synthesis of stabilizing control laws design based on IT2FLC is developed. A comparative analysis between type-1 fuzzy logic controller (T1FLC) and IT2FLC of the DFIM is shown. Simulation results show the feasibility and the effectiveness of the suggested method to the control of the DFIM under different operating conditions such as load torque and in the presence of parameters variation. [ABSTRACT FROM AUTHOR]

Establishing trust and reputation for evaluation of message reliability is key to the vehicular ad hoc networks (VANETs). Most of the previous reputation management systems focus on the effectiveness of the reputation management system in handling the liars who send false service messages. However, these reputation management systems have two drawbacks. One is that they are vulnerable to tactical attacks such as self-promoting attacks and bad-mouthing attacks. The other is that they may violate location privacy because they assume every vehicle communicates with a unique ID. Our research particularly investigates the robustness against these tactical attacks, as well as the preservation of privacy by integrating trust management with the pseudonym technique. To resist the tactical attacks in VANETs, we present a reputation model which builds both service reputation and feedback reputation. Moreover, we apply the information entropy and the majority rule to the reputation accumulation algorithms to counter false feedback. To defend the reputation link attack during pseudonym changes, we propose hidden-zone strategy and k-anonymity strategy. The simulation results show that our scheme is robust to these tactical attacks and preserves privacy against the reputation link attack during the pseudonym changes. [ABSTRACT FROM AUTHOR]

The On-Demand Multicast Routing Protocol (ODMRP) is a multicast routing protocol for mobile ad hoc networks (MANETs). Its efficiency, simplicity, and robustness against mobility render it one of the most widely used MANET multicast protocols. In this paper, we present an Adaptive On-Demand Multicast Routing Protocol (A-ODMRP), an improved version of ODMRP. ODMRP lacks a control mechanism for the physical layer. Nodes in ODMRP transmit multicast data at a fixed transmission rate and power level for the physical layer. Also, as the number of nodes belonging to the forwarding group increases, there is significant packet drop or retransmission due to interference between the nodes that send multicast data. However, A-ODMRP implements an adaptive control mechanism with a cross-layer algorithm for the physical layer. When a node transmits multicast data, A-ODMRP can adjust the transmission rate and power level of the physical layer to minimize packet drop or retransmission due to interference between nodes belonging to the forwarding group. Simulation results confirmed that A-ODMRP provides an improved goodput of up to 42% compared to ODMRP. [ABSTRACT FROM AUTHOR]

A robust H∞ control method and switched control algorithm for hydraulic actuator presents in human-machine coordinated motion to solve the motion delay of lower extremity exoskeleton. After the characteristic parameters synthesis of human limb and exoskeleton linkage, the human-machine coupled motion model is constructed to estimate the appropriate hydraulic pressure, which is considered as a structural uncertainty in hydraulic model. Then the robust controller is designed to improve the robust stability and performance under the structural and parametric uncertainty disturbances. Simulation results show that, in walking mode, this robust controller can achieve a better dynamic response and aid-force efficiency than PID controller. Then, according to gait divisions of person’s limb motion, the switched control algorithm is designed to reduce the delay of exoskeleton tracking person. Finally, the experimental results show that the human-machine coordinated walk with bearing 60 kg load and squat action with no external load are realized effectively by this proposed method. [ABSTRACT FROM AUTHOR]

The camera always suffers from image instability on the moving vehicle due to the unintentional vibrations caused by road roughness. This paper presents a novel adaptive neural network based on sliding mode control strategy to stabilize the image captured area of the camera. The purpose is to suppress vertical displacement of sprung mass with the application of active suspension system. Since the active suspension system has nonlinear and time varying characteristics, adaptive neural network (ANN) is proposed to make the controller robustness against systematic uncertainties, which release the model-based requirement of the sliding model control, and the weighting matrix is adjusted online according to Lyapunov function. The control system consists of two loops. The outer loop is a position controller designed with sliding mode strategy, while the PID controller in the inner loop is to track the desired force. The closed loop stability and asymptotic convergence performance can be guaranteed on the basis of the Lyapunov stability theory. Finally, the simulation results show that the employed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance. [ABSTRACT FROM AUTHOR]

Applying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simulation software for the early phases of building design. The author has proposed the method to minimize the magnitude of the variation in these default values in subsequent design stages. This approach maintains the accuracy of the simulation results in the initial stages of building design. In this study, a more convincing argument is presented to demonstrate the significance of the new method. The variation in the ideal default values for different building design conditions is assessed first. Next, the influence of each condition on these variations is investigated. The space depth is found to have a large impact on the ideal default value of the window to wall ratio. In addition, the presence or absence of lighting control and natural ventilation has a significant influence on the ideal default value. These effects can be used to identify the types of building conditions that should be considered to determine the ideal default values. [ABSTRACT FROM AUTHOR]

To minimize the peak sidelobe level (PSLL) of sparse concentric ring arrays, this paper presents an optimization method of grid ring radii of these arrays. The proposed method is based on modified real genetic algorithm (MGA); it makes grid ring radii as optimal variables and makes elements more reasonably distributed on the array aperture. Also, it can improve the PSLL of the sparse concentric ring arrays and can meanwhile control the computational cost. The simulated results confirming the efficiency and the robustness of the algorithm are provided at last. [ABSTRACT FROM AUTHOR]

Considering the case of autonomous underwater vehicle navigating with low speed near water surface, a new method for designing of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance under different sea conditions. Active disturbance rejection fuzzy control is applied, which is based on nonlinear motion model of autonomous underwater vehicle and the principle of zero-speed fin stabilizer. Extended state observer is used for estimation of roll motion state and unknown wave disturbance. Wave moment is counteracted by introducing compensation term into the roll control law which is founded on nonlinear feedback. Fuzzy reasoning is used for parameter adjustment of the controller online. Simulation experiments on roll motion are conducted under different sea conditions, and the results show better robustness improved by active disturbance rejection fuzzy controller of autonomous underwater vehicle navigating near water surface. [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]

Wireless signal can be easily influenced by the environment in the propagation process. The signal propagation model is the most appropriate model for current indoor environment to ensure the ranging accuracy based on received signal strength indicator (RSSI). In this paper, we propose a robust localization algorithm based on the RSSI ranging scope by which the RSSI ranging error caused by using a fixed parameter in signal propagation model is dramatically eliminated. Our contributions in this paper are twofold. First, the influence of RSSI ranging error on positioning accuracy is well discussed in detail in the scope of the wireless signal propagation model. Second, we develop a robust localization algorithm which creates a one-to-one mapping between the RSSI value and the distance scope based on the value scope of path loss exponent in the signal propagation model. Simulation results indicate that the proposed localization algorithm based on the RSSI ranging scope is robust under different environments, when the real path loss exponent is difficult to measure accurately. [ABSTRACT FROM AUTHOR]