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
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 initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjud...The initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjudgement of the design. Two conditions required by using the lifting technique are presented based on the basic formulae of the lifting. It is pointed out that only the H∞disturbance attenuation problem with no weighting functions can meet these conditions, hence, the application of the lifting technique is quite limited.展开更多
This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,th...This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,the sampleddata Takagi-Sugeno(T-S)fuzzy half-car active suspension(HCAS)system is considered,which is further modelled as a continuous system with an input delay.Firstly,considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay,a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system.Secondly,since external disturbances often belong to a restricted frequency range,a finite frequency control criterion is presented for control synthesis to reduce conservatism.Thirdly,given a full information of state variables is hardly available in practical suspension systems,a two-stage method is proposed to calculate the static output feedback control gains.Moreover,an iterative algorithm is proposed to compute the optimum solution.Finally,numerical simulations verify the effectiveness of the proposed controllers.展开更多
In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher prec...In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher precision numerical methods,and it preserves important structures of the nonlinear systems.Also,the form of Euler-Maruyama model is simple and easy to be calculated.The results provide a reference for sampled-data observer design method for such stochastic nonlinear systems,and may be useful to many practical control applications,such as tracking control in mechanical systems.And the effectiveness of the approach is demonstrated by a simulation example.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
This paper is concerned with a novel Lyapunovlike functional approach to the stability of sampled-data systems with variable sampling periods. The Lyapunov-like functional has four striking characters compared to usua...This paper is concerned with a novel Lyapunovlike functional approach to the stability of sampled-data systems with variable sampling periods. The Lyapunov-like functional has four striking characters compared to usual ones. First, it is time-dependent. Second, it may be discontinuous. Third, not every term of it is required to be positive definite. Fourth, the Lyapunov functional includes not only the state and the sampled state but also the integral of the state. By using a recently reported inequality to estimate the derivative of this Lyapunov functional, a sampled-interval-dependent stability criterion with reduced conservatism is obtained. The stability criterion is further extended to sampled-data systems with polytopic uncertainties. Finally, three examples are given to illustrate the reduced conservatism of the stability criteria.展开更多
This paper proposes a state estimation method for a class of norm bounded non linear sampled data descriptor systems using the Kalman filtering method. The descriptor model is firstly discretized to obtain a discrete ...This paper proposes a state estimation method for a class of norm bounded non linear sampled data descriptor systems using the Kalman filtering method. The descriptor model is firstly discretized to obtain a discrete time non singular one. Then a model of robust extended Kalman filter is proposed for the state estimation based on the discretized non linear non singular system. As parameters are introduced in for transforming descriptor systems into non singular ones there exist uncertainties in the state of the systems. To solve this problem an optimized upper bound is proposed so that the convergence of the estimation error co variance matrix is guaranteed in the paper. A simulating example is proposed to verify the validity of this method at last.展开更多
This paper proposes a fault estimation method for sampled data systems with sensor faults. The sampled data system is firstly discretized to obtain a discrete time model. Then a descriptor system is constructed to des...This paper proposes a fault estimation method for sampled data systems with sensor faults. The sampled data system is firstly discretized to obtain a discrete time model. Then a descriptor system is constructed to describe the discretized system with sensor faults. Based on the descriptor system representation a bank of observers are designed to isolate and estimate the sensor faults. These observers can be synthesized by the linear matrix inequality (LMI) technique and sufficient conditions for the existence of these observers are derived. Finally the effectiveness is ascertained by an aircraft simulation example which is in the proposed method.展开更多
This paper studies sampled-data consensus control of a collection of unmanned surface vehicles(USV)operating in network environments with fading channels and time-varying transmission delay.The channel fading is model...This paper studies sampled-data consensus control of a collection of unmanned surface vehicles(USV)operating in network environments with fading channels and time-varying transmission delay.The channel fading is modeled as each independent stochastic process whose probability distribution is known.By considering the effects of channel fading and transmission delay from sampler to the controller,a new MUSV system model is formulated in the framework of network.With the novel established model,stability analysis is given at first,then the sampled-data consensus controller is designed,which also extends to the robust control with wave-induced disturbance.The effectiveness of the presented method is demonstrated by numerical simulation.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
In this paper, a robust sensor fault diagnosis observer with non-singular structure is proposed for a class of linear sampled-data descriptor system with state time-vary delay. Firstly, a sampled-data descriptor model...In this paper, a robust sensor fault diagnosis observer with non-singular structure is proposed for a class of linear sampled-data descriptor system with state time-vary delay. Firstly, a sampled-data descriptor model with time-vary delay is proposed and transformed into a discrete-time non-singular one. Then, a robust sensor fault diagnosis observer is proposed based on the state estimation error and the measurement residual, this observer can guarantee the robustness of the residual against the augmented disturbance and the sensor fault, which means the H∞ performance index is satisfied. As the confining matrix of the designed observer parameters does not meet the Linear Matrix Inequality (LMI), a cone complementary linearization (CCL) algorithm is proposed to solve this problem. The decision logic of the residual is obtained by the residual evaluation function. Simulation results show the effectiveness of the method.展开更多
This paper investigates the stability problem for sampled-data systems by adopting a refined semi-looped-functional,which is with the following two improvements.Firstly,the new functional term is with a new integral v...This paper investigates the stability problem for sampled-data systems by adopting a refined semi-looped-functional,which is with the following two improvements.Firstly,the new functional term is with a new integral vectorη0,which contains sampling information of the systems and associates two commonly used vectors.Secondly,the vectorη0 is combined into various zero equations for processing the functional,especially where a new equation is derived fromη0.Based on the refined functional,further stability results for sampled-data systems are obtained.And the effectiveness of the results is numerically verified through two examples at the end.展开更多
This paper studies the issue of observer-based feedback stabilisation for a class of linear sampleddatasystems with model uncertainty and external disturbance. First, for a sampled-data systemwith external disturbance...This paper studies the issue of observer-based feedback stabilisation for a class of linear sampleddatasystems with model uncertainty and external disturbance. First, for a sampled-data systemwith external disturbance, a sampled-data observer is designed to estimate the system state.Subsequently, a robust H∞ controller based on the observer is developed. For a continuous samplinginterval, the gain matrices of both observer and controller change exponentially. Second,using the state coordinate transformations with an exponential rate, a unified dynamics is constructedby augmenting the state estimation error and the closed-loop system state as a newstate. Next, the sufficient conditions ensuring the asymptotical stability of the closed-loop systemare given by the Lyapunov–Krasovskii method and linear matrix inequality (LMI) technique.Finally, the effectiveness of the proposed method is verified by a helicopter model.展开更多
We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switch...We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switched Boolean network(SBN),and further global stability of the BCN under ASDC can be obtained by studying the global stability of the transformed SBN.Unfortunately,since the major idea of our previous work is to use stable subsystems to offset the state divergence caused by unstable subsystems,the SBN considered has at least one stable subsystem.The central thought in this paper is that switching behavior also has good stabilization;i.e.,the SBN can also be stable with appropriate switching laws designed,even if all subsystems are unstable.This is completely different from that in our previous work.Specifically,for this case,the dwell time(DT)should be limited within a pair of upper and lower bounds.By means of the discretized Lyapunov function and DT,a sufficient condition for global stability is obtained.Finally,the above results are demonstrated by a biological example.展开更多
This paper is concerned with control and optimization for a sampled-data system with quantization and actuator saturation. Based quantization and actuator saturation a controller is introduced. The corresponding close...This paper is concerned with control and optimization for a sampled-data system with quantization and actuator saturation. Based quantization and actuator saturation a controller is introduced. The corresponding closed loop system is transformed into a system with input saturation and bounded external disturbance. A new Lyapunov functional is constructed to derive a sample-interval dependent condition on the existence of a state feedback controller such that the closed-loop system is exponentially convergent to an ultimate ellipsoid for the initial condition starting from some initial ellipsoid. Based on the condition, the desired controller is designed. Furthermore, optimization problems about the sample-interval, the ultimate ellipsoid and the initial ellipsoid are formulated. An example is given to illustrate the effectiveness of the proposed method.展开更多
This paper investigates the semi-global robust output regulation problem for a class of uncertain nonlinear systems via a sampled-data output feedback control law.What makes the results interesting is that the nonline...This paper investigates the semi-global robust output regulation problem for a class of uncertain nonlinear systems via a sampled-data output feedback control law.What makes the results interesting is that the nonlinearities of the proposed system do not have to satisfy linear growth condition and the uncertain parameters of our system are allowed to belong to some arbitrarily large prescribed compact subset.Two cases are considered.The first case is that the exogenous signal is constant.The second case is that the exogenous signal is time-varying and bounded.For the first case,the authors solve the problem exactly in the sense that the tracking error approaches zero asymptotically.For the second case,the authors solve the problem practically in the sense that the steady-state tracking error can be made arbitrarily small.Finally,an example is given to illustrate the effectiveness of our approach.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
The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learn...The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learning controller for a real application and reduce the memory size for implementation, a current error based sampled-data proportional-derivative(PD) type iterative learning controller is proposed for control systems with initial resetting error, input disturbance and output measurement noise in this paper.The proposed iterative learning controller is simple and effective. The first contribution in this paper is to prove the learning error convergence via a rigorous technical analysis. It is shown that the learning error will converge to a residual set if a forgetting factor is introduced in the controller. All the theoretical results are also shown by computer simulations. The second main contribution is to realize the iterative learning controller by a digital circuit using a field programmable gate array(FPGA) chip applied to repetitive position tracking control of direct current(DC) motors. The feasibility and effectiveness of the proposed current error based sampleddata iterative learning controller are demonstrated by the experiment results. Finally, the relationship between learning performance and design parameters are also discussed extensively.展开更多
This paper investigates sampling dependent stability for aperiodic sampled-data systems by employing a Lyapunov-like functional that is time-dependent,and not imposed to be definite positive.Based on the system inform...This paper investigates sampling dependent stability for aperiodic sampled-data systems by employing a Lyapunov-like functional that is time-dependent,and not imposed to be definite positive.Based on the system information on the sampling interval wholly rather than partly,a new Lyapunovlike functional is constructed,which extends existing ones by introducing the integral of the system state and the cross terms among this integral and the sampled state.To take advantage of the integral of the system state,integral equations of the sampled-data system are explored when estimating the derivative of the extended functional.By the Lyapunov-like functional theory,a new sampling dependent stability result is obtained for sampled-data systems without uncertainties.Then,the stability result is applied to sampled-data systems with polytopic uncertainties and a robust stability result is derived.At last,numerical examples are given to illustrate that the stability results improve over some existing ones.展开更多
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 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Supported by the Harbin Engineering University Fund for Basic Projects (heuft06041)
文摘The initial motivation of the lifting technique is to solve the H∞control problems. However, the conventional weighted H∞design does not meet the conditions required by lifting, so the result often leads to a misjudgement of the design. Two conditions required by using the lifting technique are presented based on the basic formulae of the lifting. It is pointed out that only the H∞disturbance attenuation problem with no weighting functions can meet these conditions, hence, the application of the lifting technique is quite limited.
基金supported by the National Natural Science Foundation of China(51705084)the Natural Science Foundation of Guangdong Province of China(2018A030313999,2019A1515011602)+2 种基金the Fundamental Research Funds for the Central Universities(2018MS46,N2003032)the Opening Project of Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing,South China University of Technology(2019kfkt06)the Research Grants of the University of Macao(MYRG2017-00135-FST,MYRG2019-00028-FST)。
文摘This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,the sampleddata Takagi-Sugeno(T-S)fuzzy half-car active suspension(HCAS)system is considered,which is further modelled as a continuous system with an input delay.Firstly,considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay,a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system.Secondly,since external disturbances often belong to a restricted frequency range,a finite frequency control criterion is presented for control synthesis to reduce conservatism.Thirdly,given a full information of state variables is hardly available in practical suspension systems,a two-stage method is proposed to calculate the static output feedback control gains.Moreover,an iterative algorithm is proposed to compute the optimum solution.Finally,numerical simulations verify the effectiveness of the proposed controllers.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2014AA06A503)the National Natural Science Foundation of China(61422307,61673361)+3 种基金the Scientific Research Starting Foundation for the Returned Overseas Chinese Scholars and Ministry of Education of Chinasupports from the Youth Top-notch Talent Support Programthe 1000-talent Youth Programthe Youth Yangtze River Scholarship
文摘In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher precision numerical methods,and it preserves important structures of the nonlinear systems.Also,the form of Euler-Maruyama model is simple and easy to be calculated.The results provide a reference for sampled-data observer design method for such stochastic nonlinear systems,and may be useful to many practical control applications,such as tracking control in mechanical systems.And the effectiveness of the approach is demonstrated by a simulation example.
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supported by the National Natural Science Foundation of China(61374090)the Program for Scientific Research Innovation Team in Colleges and Universities of Shandong Provincethe Taishan Scholarship Project of Shandong Province
文摘This paper is concerned with a novel Lyapunovlike functional approach to the stability of sampled-data systems with variable sampling periods. The Lyapunov-like functional has four striking characters compared to usual ones. First, it is time-dependent. Second, it may be discontinuous. Third, not every term of it is required to be positive definite. Fourth, the Lyapunov functional includes not only the state and the sampled state but also the integral of the state. By using a recently reported inequality to estimate the derivative of this Lyapunov functional, a sampled-interval-dependent stability criterion with reduced conservatism is obtained. The stability criterion is further extended to sampled-data systems with polytopic uncertainties. Finally, three examples are given to illustrate the reduced conservatism of the stability criteria.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61021002)
文摘This paper proposes a state estimation method for a class of norm bounded non linear sampled data descriptor systems using the Kalman filtering method. The descriptor model is firstly discretized to obtain a discrete time non singular one. Then a model of robust extended Kalman filter is proposed for the state estimation based on the discretized non linear non singular system. As parameters are introduced in for transforming descriptor systems into non singular ones there exist uncertainties in the state of the systems. To solve this problem an optimized upper bound is proposed so that the convergence of the estimation error co variance matrix is guaranteed in the paper. A simulating example is proposed to verify the validity of this method at last.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61004038)
文摘This paper proposes a fault estimation method for sampled data systems with sensor faults. The sampled data system is firstly discretized to obtain a discrete time model. Then a descriptor system is constructed to describe the discretized system with sensor faults. Based on the descriptor system representation a bank of observers are designed to isolate and estimate the sensor faults. These observers can be synthesized by the linear matrix inequality (LMI) technique and sufficient conditions for the existence of these observers are derived. Finally the effectiveness is ascertained by an aircraft simulation example which is in the proposed method.
基金Project supported by Key Laboratory of Intelligent Perception and Advanced Control of State Ethnic Affairs Commission MD-IPAC-2019401National Natural Science Foundation of China under 61703072 and 61673084.
文摘This paper studies sampled-data consensus control of a collection of unmanned surface vehicles(USV)operating in network environments with fading channels and time-varying transmission delay.The channel fading is modeled as each independent stochastic process whose probability distribution is known.By considering the effects of channel fading and transmission delay from sampler to the controller,a new MUSV system model is formulated in the framework of network.With the novel established model,stability analysis is given at first,then the sampled-data consensus controller is designed,which also extends to the robust control with wave-induced disturbance.The effectiveness of the presented method is demonstrated by numerical simulation.
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Sponsored by the National Natural Science Foundation of China(Grant No.61021002)
文摘In this paper, a robust sensor fault diagnosis observer with non-singular structure is proposed for a class of linear sampled-data descriptor system with state time-vary delay. Firstly, a sampled-data descriptor model with time-vary delay is proposed and transformed into a discrete-time non-singular one. Then, a robust sensor fault diagnosis observer is proposed based on the state estimation error and the measurement residual, this observer can guarantee the robustness of the residual against the augmented disturbance and the sensor fault, which means the H∞ performance index is satisfied. As the confining matrix of the designed observer parameters does not meet the Linear Matrix Inequality (LMI), a cone complementary linearization (CCL) algorithm is proposed to solve this problem. The decision logic of the residual is obtained by the residual evaluation function. Simulation results show the effectiveness of the method.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62221004 and 62073166the Shandong Provincial Natural Science Foundation under Grant No.ZR2021ZD13+1 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.KYCX230473the Project on the Technological Leading Talent Teams Led by Frontiers Science Center for Complex Equipment System Dynamics under Grant No.FSCCESD220401。
文摘This paper investigates the stability problem for sampled-data systems by adopting a refined semi-looped-functional,which is with the following two improvements.Firstly,the new functional term is with a new integral vectorη0,which contains sampling information of the systems and associates two commonly used vectors.Secondly,the vectorη0 is combined into various zero equations for processing the functional,especially where a new equation is derived fromη0.Based on the refined functional,further stability results for sampled-data systems are obtained.And the effectiveness of the results is numerically verified through two examples at the end.
基金the National Nature Science Foundation of China[grant number 61973105]in part by the Fundamental Research Funds for the Universities of Henan Province[grant number NSFRF180335]+3 种基金in part by the Innovative Scientists and Technicians Team of Henan Provincial High Education[grant number 20IRTSTHN019]in part by the Innovative Scientists and Technicians Team of Henan Polytechnic University[grant number T2019-2]in part by the Innovation Scientists and Technicians Troop Construction Projects of Henan Province[grant number CXTD2016054]in part by the Zhongyuan high level talents special support plan[grant number ZYQR201912031].
文摘This paper studies the issue of observer-based feedback stabilisation for a class of linear sampleddatasystems with model uncertainty and external disturbance. First, for a sampled-data systemwith external disturbance, a sampled-data observer is designed to estimate the system state.Subsequently, a robust H∞ controller based on the observer is developed. For a continuous samplinginterval, the gain matrices of both observer and controller change exponentially. Second,using the state coordinate transformations with an exponential rate, a unified dynamics is constructedby augmenting the state estimation error and the closed-loop system state as a newstate. Next, the sufficient conditions ensuring the asymptotical stability of the closed-loop systemare given by the Lyapunov–Krasovskii method and linear matrix inequality (LMI) technique.Finally, the effectiveness of the proposed method is verified by a helicopter model.
基金Project supported by the Natural Science Foundation of Jiangsu Province,China(No.BK20170019)the Fundamental Research Funds for the Central Universities+2 种基金the National Natural Science Foundation of China(Nos.61973078,61573102,and 11671158)Hong Kong RGC GRF,China(No.17301519)IMR and RAE Research Fund from Faculty of Science,HKU,China。
文摘We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switched Boolean network(SBN),and further global stability of the BCN under ASDC can be obtained by studying the global stability of the transformed SBN.Unfortunately,since the major idea of our previous work is to use stable subsystems to offset the state divergence caused by unstable subsystems,the SBN considered has at least one stable subsystem.The central thought in this paper is that switching behavior also has good stabilization;i.e.,the SBN can also be stable with appropriate switching laws designed,even if all subsystems are unstable.This is completely different from that in our previous work.Specifically,for this case,the dwell time(DT)should be limited within a pair of upper and lower bounds.By means of the discretized Lyapunov function and DT,a sufficient condition for global stability is obtained.Finally,the above results are demonstrated by a biological example.
基金supported by the Natural Science Foundation of China under Grant Nos.61374090,and 61473171the Program for Scientific Research Innovation Team in Colleges and Universities of Shandong Provincethe Taishan Scholarship Project of Shandong Province
文摘This paper is concerned with control and optimization for a sampled-data system with quantization and actuator saturation. Based quantization and actuator saturation a controller is introduced. The corresponding closed loop system is transformed into a system with input saturation and bounded external disturbance. A new Lyapunov functional is constructed to derive a sample-interval dependent condition on the existence of a state feedback controller such that the closed-loop system is exponentially convergent to an ultimate ellipsoid for the initial condition starting from some initial ellipsoid. Based on the condition, the desired controller is designed. Furthermore, optimization problems about the sample-interval, the ultimate ellipsoid and the initial ellipsoid are formulated. An example is given to illustrate the effectiveness of the proposed method.
基金the Research Grants Council of the Hong Kong Special Administration Region under Grant No.14202619the National Natural Science Foundation of China under Grant No.61633007the National Natural Science Foundation of China under Grant No.61973260。
文摘This paper investigates the semi-global robust output regulation problem for a class of uncertain nonlinear systems via a sampled-data output feedback control law.What makes the results interesting is that the nonlinearities of the proposed system do not have to satisfy linear growth condition and the uncertain parameters of our system are allowed to belong to some arbitrarily large prescribed compact subset.Two cases are considered.The first case is that the exogenous signal is constant.The second case is that the exogenous signal is time-varying and bounded.For the first case,the authors solve the problem exactly in the sense that the tracking error approaches zero asymptotically.For the second case,the authors solve the problem practically in the sense that the steady-state tracking error can be made arbitrarily small.Finally,an example is given to illustrate the effectiveness of our approach.
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supported by National Science Council,Taiwan,China(No.NSC102-2221-E-211-011)National Nature Science Foundation of China(No.61374102)
文摘The design of iterative learning controller(ILC) requires to store the system input, output or control parameters of previous trials for generating the input of the current trial. In order to apply the iterative learning controller for a real application and reduce the memory size for implementation, a current error based sampled-data proportional-derivative(PD) type iterative learning controller is proposed for control systems with initial resetting error, input disturbance and output measurement noise in this paper.The proposed iterative learning controller is simple and effective. The first contribution in this paper is to prove the learning error convergence via a rigorous technical analysis. It is shown that the learning error will converge to a residual set if a forgetting factor is introduced in the controller. All the theoretical results are also shown by computer simulations. The second main contribution is to realize the iterative learning controller by a digital circuit using a field programmable gate array(FPGA) chip applied to repetitive position tracking control of direct current(DC) motors. The feasibility and effectiveness of the proposed current error based sampleddata iterative learning controller are demonstrated by the experiment results. Finally, the relationship between learning performance and design parameters are also discussed extensively.
基金the Natural Science Foundation of China under Grant No.61374090the Program for Scientific Research Innovation Team in Colleges and Universities of Shandong Provincethe Taishan Scholarship Project of Shandong Province。
文摘This paper investigates sampling dependent stability for aperiodic sampled-data systems by employing a Lyapunov-like functional that is time-dependent,and not imposed to be definite positive.Based on the system information on the sampling interval wholly rather than partly,a new Lyapunovlike functional is constructed,which extends existing ones by introducing the integral of the system state and the cross terms among this integral and the sampled state.To take advantage of the integral of the system state,integral equations of the sampled-data system are explored when estimating the derivative of the extended functional.By the Lyapunov-like functional theory,a new sampling dependent stability result is obtained for sampled-data systems without uncertainties.Then,the stability result is applied to sampled-data systems with polytopic uncertainties and a robust stability result is derived.At last,numerical examples are given to illustrate that the stability results improve over some existing ones.