In this paper, we study the exponential synchronization of chaotic Lur＇e systems with time-varying delays via sampled-data control by using sector nonlinearties. In order to make full use of information about samplin...In this paper, we study the exponential synchronization of chaotic Lur＇e systems with time-varying delays via sampled-data control by using sector nonlinearties. In order to make full use of information about sampling intervals and interval time-varying delays, new Lyapunov-Krasovskii functionals with triple integral terms are introduced. Based on the convex combination technique, two kinds of synchronization criteria are derived in terms of linear matrix inequal- ities, which can be efficiently solved via standard numerical software. Finally, three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.展开更多
Reinforcement Learning(RL)based control algorithms can learn the control strategies for nonlinear and uncertain environment during interacting with it.Guided by the rewards generated by environment,a RL agent can lear...Reinforcement Learning(RL)based control algorithms can learn the control strategies for nonlinear and uncertain environment during interacting with it.Guided by the rewards generated by environment,a RL agent can learn the control strategy directly in a model-free way instead of investigating the dynamic model of the environment.In the paper,we propose the sampled-data RL control strategy to reduce the computational demand.In the sampled-data control strategy,the whole control system is of a hybrid structure,in which the plant is of continuous structure while the controller(RL agent)adopts a discrete structure.Given that the continuous states of the plant will be the input of the agent,the state–action value function is approximated by the fully connected feed-forward neural networks(FCFFNN).Instead of learning the controller at every step during the interaction with the environment,the learning and acting stages are decoupled to learn the control strategy more effectively through experience replay.In the acting stage,the most effective experience obtained during the interaction with the environment will be stored and during the learning stage,the stored experience will be replayed to customized times,which helps enhance the experience replay process.The effectiveness of proposed approach will be verified by simulation examples.展开更多
The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state an...The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state and the input control matrices. By applying an input delay approach, the system was transformed into a continuous time-delay system. Attention was focused on the design of a robust guaranteed cost sampled-data control law which guarantees that the closed-loop system is asymptotically stable and the quadratic performance index is less than a certain bound for all admissible uncertainties. By applying Lyapunov stability theory, the theorems were derived to provide sufficient conditions for the existence of robust guaranteed cost sampled-data control law in the form of linear matrix inequalities (LMIs), especially an optimal state-feedback guaranteed cost sampled-data control law which ensures the minimization of the guaranteed cost was given. The effectiveness of the proposed method was illustrated by a simulation example with the asymptotically stable curves of system state under the initial condition of x(0)=[0.679 6 0].展开更多
This paper examines the stabilization problem of a distributed networked control system under the effect of cyberattacks by employing a hybrid aperiodic triggering mechanism.The cyber-attack considered in the paper is...This paper examines the stabilization problem of a distributed networked control system under the effect of cyberattacks by employing a hybrid aperiodic triggering mechanism.The cyber-attack considered in the paper is a stochastic deception attack at the sensor-controller end. The probability of the occurrence of attack on a subsystem is represented using a random variable. A decentralized hybrid sampled-data strategy is introduced to save energy consumption and reduce the transmission load of the network. In the proposed decentralized strategy, each subsystem can decide independently whether its state should be transmitted to the controller or not. The scheme of the hybrid triggering mechanism for each subsystem composed of two stages: In the first stage, the next sampling instant is computed using a self-triggering strategy. Subsequently, in the second stage, an event-triggering condition is checked at these sampling instants and the control signal is computed only if the event-triggering condition is violated. The self-triggering condition used in the first stage is dependent on the selection of eventtriggering condition of the second stage. Finally, a comparison of the proposed approach with other triggering mechanisms existing in the literature is presented in terms of the sampling instants,transmission frequency and performance measures through simulation examples.展开更多
We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-d...We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality （LMI） approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions （e.g., time derivative is smaller than one） are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.展开更多
In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotica...In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.展开更多
A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP sh...A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.展开更多
This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov functional approach, is adopte...This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov functional approach, is adopted in constructing the Lyapunov functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality（LMI） technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.展开更多
For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is continuously distributed in a given interval, is described as a multiple independent and identically distributed (i....For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is continuously distributed in a given interval, is described as a multiple independent and identically distributed (i.i.d.) process. With this process, the closed-loop system is transformed into an asynchronous dynamical impulsive model with input delays. Sufficient conditions for the closed-loop mean-square exponential stability are presented in terms of linear matrix inequalities (LMIs), in which the relation between the nonuniform sampling and the mean-square exponential stability of the closed-loop system is explicitly established. Based on the stability conditions, the controller design method is given, which is further formulated as a convex optimization problem with LMI constraints. Numerical examples and experiment results are given to show the effectiveness and the advantages of the theoretical results.展开更多
The basic analysis and synthesis approaches for multirate sampled-data control system are reviewed. After giving the definition and some properties of multirate system are given, its origination, development and desig...The basic analysis and synthesis approaches for multirate sampled-data control system are reviewed. After giving the definition and some properties of multirate system are given, its origination, development and design methods are discussed in detail. Finally, some remarks, expectations and conclusions on the present research status and the research directions are given.展开更多
This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder ma...This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder may result in the performance degradation of the observer.In this paper,an improved predictor-based observer is designed to compensate for the influence of the unmeasurable states,sampling errors and output delay.In addition,a sampled-data output-feedback controller is also constructed using the gain scaling technique.By the Lyapunov-Krasovskii functional method,the global exponential stability of the resulting closed-loop system can be guaranteed under some sufficient conditions.The simulation results are provided to demonstrate the main results.展开更多
This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus...This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.展开更多
The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.展开更多
Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the s...Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.展开更多
Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilizatio...Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.展开更多
This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic mo...This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.展开更多
Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these...Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford...Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.展开更多
文摘In this paper, we study the exponential synchronization of chaotic Lur＇e systems with time-varying delays via sampled-data control by using sector nonlinearties. In order to make full use of information about sampling intervals and interval time-varying delays, new Lyapunov-Krasovskii functionals with triple integral terms are introduced. Based on the convex combination technique, two kinds of synchronization criteria are derived in terms of linear matrix inequal- ities, which can be efficiently solved via standard numerical software. Finally, three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.
基金supported by Imperial College London,UK,King’s College London,UK and Engineering and Physical Sciences Research Council(EPSRC),UK.
文摘Reinforcement Learning(RL)based control algorithms can learn the control strategies for nonlinear and uncertain environment during interacting with it.Guided by the rewards generated by environment,a RL agent can learn the control strategy directly in a model-free way instead of investigating the dynamic model of the environment.In the paper,we propose the sampled-data RL control strategy to reduce the computational demand.In the sampled-data control strategy,the whole control system is of a hybrid structure,in which the plant is of continuous structure while the controller(RL agent)adopts a discrete structure.Given that the continuous states of the plant will be the input of the agent,the state–action value function is approximated by the fully connected feed-forward neural networks(FCFFNN).Instead of learning the controller at every step during the interaction with the environment,the learning and acting stages are decoupled to learn the control strategy more effectively through experience replay.In the acting stage,the most effective experience obtained during the interaction with the environment will be stored and during the learning stage,the stored experience will be replayed to customized times,which helps enhance the experience replay process.The effectiveness of proposed approach will be verified by simulation examples.
基金Project(12511109) supported by the Science and Technology Studies Foundation of Heilongjiang Educational Committee of 2011, China
文摘The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state and the input control matrices. By applying an input delay approach, the system was transformed into a continuous time-delay system. Attention was focused on the design of a robust guaranteed cost sampled-data control law which guarantees that the closed-loop system is asymptotically stable and the quadratic performance index is less than a certain bound for all admissible uncertainties. By applying Lyapunov stability theory, the theorems were derived to provide sufficient conditions for the existence of robust guaranteed cost sampled-data control law in the form of linear matrix inequalities (LMIs), especially an optimal state-feedback guaranteed cost sampled-data control law which ensures the minimization of the guaranteed cost was given. The effectiveness of the proposed method was illustrated by a simulation example with the asymptotically stable curves of system state under the initial condition of x(0)=[0.679 6 0].
文摘This paper examines the stabilization problem of a distributed networked control system under the effect of cyberattacks by employing a hybrid aperiodic triggering mechanism.The cyber-attack considered in the paper is a stochastic deception attack at the sensor-controller end. The probability of the occurrence of attack on a subsystem is represented using a random variable. A decentralized hybrid sampled-data strategy is introduced to save energy consumption and reduce the transmission load of the network. In the proposed decentralized strategy, each subsystem can decide independently whether its state should be transmitted to the controller or not. The scheme of the hybrid triggering mechanism for each subsystem composed of two stages: In the first stage, the next sampling instant is computed using a self-triggering strategy. Subsequently, in the second stage, an event-triggering condition is checked at these sampling instants and the control signal is computed only if the event-triggering condition is violated. The self-triggering condition used in the first stage is dependent on the selection of eventtriggering condition of the second stage. Finally, a comparison of the proposed approach with other triggering mechanisms existing in the literature is presented in terms of the sampling instants,transmission frequency and performance measures through simulation examples.
基金the Ministry of Science and Technology of India(Grant No.DST/Inspire Fellowship/2010/[293]/dt.18/03/2011)
文摘We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality （LMI） approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions （e.g., time derivative is smaller than one） are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 50977008,60774048,and 60774093)the National High Technology Research and Development Program of China (Grant No. 2009AA04Z127)+1 种基金the Special Grant of Financial Support from China Postdoctoral Science Foundation (Grant No. 200902547)Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 200801451096)
文摘In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.
基金the National Natural Science Foundation of China(No.51579114)the Project of New Century Excellent Talents of Colleges and Universities of Fujian Province(No.JA12181)the Project of Young and Middle-Aged Teacher Education of Fujian Province(No.JAT170309)
文摘A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.
基金Project supported by the National Natural Science Foundation of China(Grant No.61304064)the Scientific Research Fund of Hunan Provincial Education Department,China(Grant Nos.15B067 and 16C0475)a Discovering Grant from Australian Research Council
文摘This paper is concerned with the synchronization of delayed neural networks via sampled-data control. A new technique, namely, the free-matrix-based time-dependent discontinuous Lyapunov functional approach, is adopted in constructing the Lyapunov functional, which takes advantage of the sampling characteristic of sawtooth input delay. Based on this discontinuous Lyapunov functional, some less conservative synchronization criteria are established to ensure that the slave system is synchronous with the master system. The desired sampled-data controller can be obtained through the use of the linear matrix inequality（LMI） technique. Finally, two numerical examples are provided to demonstrate the effectiveness and the improvements of the proposed methods.
基金supported by National Natural Science Foundation of China (Nos.61104105,U0735003 and 60974047)Natural Science Foundation of Guangdong Province of China (No.9451009001002702)
文摘For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is continuously distributed in a given interval, is described as a multiple independent and identically distributed (i.i.d.) process. With this process, the closed-loop system is transformed into an asynchronous dynamical impulsive model with input delays. Sufficient conditions for the closed-loop mean-square exponential stability are presented in terms of linear matrix inequalities (LMIs), in which the relation between the nonuniform sampling and the mean-square exponential stability of the closed-loop system is explicitly established. Based on the stability conditions, the controller design method is given, which is further formulated as a convex optimization problem with LMI constraints. Numerical examples and experiment results are given to show the effectiveness and the advantages of the theoretical results.
文摘The basic analysis and synthesis approaches for multirate sampled-data control system are reviewed. After giving the definition and some properties of multirate system are given, its origination, development and design methods are discussed in detail. Finally, some remarks, expectations and conclusions on the present research status and the research directions are given.
基金supported by the Autonomous Innovation Team Foundation for“20 Items of the New University”of Jinan City(202228087)the National Natural Science Foundation of China(62073190).
文摘This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder may result in the performance degradation of the observer.In this paper,an improved predictor-based observer is designed to compensate for the influence of the unmeasurable states,sampling errors and output delay.In addition,a sampled-data output-feedback controller is also constructed using the gain scaling technique.By the Lyapunov-Krasovskii functional method,the global exponential stability of the resulting closed-loop system can be guaranteed under some sufficient conditions.The simulation results are provided to demonstrate the main results.
文摘This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
基金supported in part by the National Natural Science Foundation of China under Grant 52077002。
文摘Model predictive control(MPC)has been deemed as an attractive control method in motor drives by virtue of its simple structure,convenient multi-objective optimization,and satisfactory dynamic performance.However,the strong reliance on mathematical models seriously restrains its practical application.Therefore,improving the robustness of MPC has attained significant attentions in the last two decades,followed by which,model-free predictive control(MFPC)comes into existence.This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation.Based on this review,the principles of the reported MFPC strategies are introduced in detail,as well as the challenges encountered in technology realization.In addition,some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features.Finally,the future trends of MFPC are discussed based on the current state and reported developments.
基金supported by Scientific Research Projects of China Association of Metros(CAMET-KY-2022039)State Key Laboratory of Traction and Control System of EMU and Locomotive(2023YJ386).
文摘Purpose–This study aims to propose a cooperative adhesion control method for trains with multiple motors electric locomotives.The method is intended to optimize the output torque of each motor,maximize the utilization of train adhesion within the total torque command,reduce the train skidding/sliding phenomenon and achieve optimal adhesion utilization for each axle,thus realizing the optimal allocation of the multi-motor electric locomotives.Design/methodology/approach–In this study,a model predictive control(MPC)-based cooperative maximum adhesion tracking control method for multi-motor electric locomotives is presented.Firstly,train traction system with multiple motors is constructed in accordance with Newton’s second law.These equations include the train dynamics equations,the axle dynamics equations,and the wheel-rail adhesion coefficient equations.Then,a new MPC-based multi-axle adhesion co-optimization method is put forward.This method calculates the optimal output torque through real-time iteration based on the known reference slip speed to achieve multi-axle co-optimization under different circumstances.Findings–This paper presents a MPC system designed for the cooperative control of multi-axle adhesion.The results indicate that the proposed control system is able to optimize the adhesion of multiple axles under numerous different conditions and achieve the optimal power distribution based on the reduction of train skidding/sliding.Originality/value–This study presents a novel cooperative adhesion tracking control scheme.It is designed for multi-motor electric locomotives,which has rarely been studied before.And simulations are carried out in different conditions,including variable surfaces and motor failing.
基金supported by the National Natural Science Foundation of China(Nos.62103052 and No.52175214)。
文摘This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.
基金supported by the Fundamental Research Funds for Central Public Welfare Research Institute,No.2020CZ-5(to WS and GS)the National Natural Science Foundation of China,No.31970970(to JSR)Fundamental Research Funds for the Central Universities,No.YWF-23-YG-QB-010(to JSR)。
文摘Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury level.However,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface electromyography.In this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord injury.Eleven patients with chronic complete thoracic spinal cord injury were recruited.Surface electromyography data from eight major leg muscles were acquired and compared before and after the passive activity protocol.The results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of activation.Although the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically significant.These findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported in part by the Universitat Politècnica de València under grant PAID-10-21supported through AMRITA Seed Grant(Proposal ID:ASG2022188)。
文摘Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.
