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
A novel adaptive neural network （NN） output-feedback regulation algorithm for a class of nonlinear time-varying timedelay systems is proposed. Both the designed observer and controller are independent of time delay....A novel adaptive neural network （NN） output-feedback regulation algorithm for a class of nonlinear time-varying timedelay systems is proposed. Both the designed observer and controller are independent of time delay. Different from the existing results, where the upper bounding functions of time-delay terms are assumed to be known, we only use an NN to compensate for all unknown upper bounding functions without that assumption. The proposed design method is proved to be able to guarantee semi-global uniform ultimate boundedness of all the signals in the closed system, and the system output is proved to converge to a small neighborhood of the origin. The simulation results verify the effectiveness of the control scheme.展开更多
In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let ...In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control(DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.展开更多
In this paper, the output tracking control is investigated for a class of nonlinear systems when only output is available for feedback. Based on the multivariable analog of circle criterion, an observer is first intro...In this paper, the output tracking control is investigated for a class of nonlinear systems when only output is available for feedback. Based on the multivariable analog of circle criterion, an observer is first introduced. Then, the observer-based output tracking controller is constructively designed by using the integral backstepping approach together with completing square. It is shown that, under relatively mild conditions, all the closed-loop signals are uniformly bounded. Meanwhile the system output asymptotically tracks the desired output. A simulation example is given to illustrate the effectiveness of the theoretical results.展开更多
This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. ...This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.展开更多
An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems.Both the designed observer and controller are free from time de...An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems.Both the designed observer and controller are free from time delays.Different from the existing results,this paper need not the assumption that the upper bounding functions of time-delay terms are known,and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms,so the designed controller procedure is more simplified.In addition,the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded,and the output regulation error converges to a small residual set around the origin.Two simulation examples are provided to verify the effectiveness of control scheme.展开更多
For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic non- linear output-feedback systems. Different from the existing results, the nonlinear terms are assum...For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic non- linear output-feedback systems. Different from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate for all unknown nonlinear functions so that the controller design is more simplified. Based on stochastic LaSalle theorem, the resulted closed-loop system is proved to be globally asymptotically stable in probability. The simulation results further verify the effectiveness of the control scheme.展开更多
The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear...The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.展开更多
This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the co...This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the consensus goal,each agent estimates its state through a Luenberger observer,exchanges its estimated state with neighbors,and constructs the control input with the estimated states of its own and neighbors.Due to the existence of observation and process noises,only practical consensus,instead of asymptotical consensus,can be achieved in such multi-agent systems.The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents.That performance is closely related to the observation gains of the state observers and the control gains of agents.This paper proposes a method to optimize such performance with respect to the concerned observation and control gains.That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities(LMIs).Solving these LMIs gives some intermediate matrix variables.By perturbing observation and control gains,and the intermediate matrix variables,the original LMIs yield another group of LMIs,which can be solved to provide a descent direction of observation and control gains.Moving along that descent direction,observation and control gains can be improved to yield better performance and work as the starting point of the next iteration.By iteratively repeating this procedure,we can hopefully improve the consensus performance of the concerned multi-agent system.Simulations are done to demonstrate the effectiveness of the proposed method.展开更多
The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system state...The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system states and hence the dynamical equations that the estimation error satisfies are derived first. Then, by using integral backstepping approach together with completing square technique, the output-feedback stabilization control is constructively designed such that the closed-loop system is asymptotically stable. Finally, an example is given to illustrate the main results of this paper.展开更多
This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control syst...This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control system is exploited to establish a two-dimensional （2D） model that converts the design problem into a robust stabilization problem for a discrete 2D system. By employing Lyapunov stability theory and the singular-value decomposition of the output matrix, a linear-matrix-inequality （LMI） based stability condition is derived. The condition can be used directly to design the gains of the repetitive controller. Two tuning parameters in the LMI enable the preferential adjustment of control and learning. A numerical example illustrates the design procedure and demonstrates the validity of the method.展开更多
The article addresses the output-feedback control issue for a class of multi-input multi-output(MIMO)uncertain nonlinear systems with multiple event-triggered mechanisms(ETM).Compared to previous event-triggering stud...The article addresses the output-feedback control issue for a class of multi-input multi-output(MIMO)uncertain nonlinear systems with multiple event-triggered mechanisms(ETM).Compared to previous event-triggering studies,this paper aims to trigger both the output and filtered signals.Unknown nonlinear dynamics are approximated using fuzzy logic systems(FLSs).Then,a novel kind of state observer has been designed to deal with unmeasurable state problems using the triggered output signal.The sampled estimated state,the triggered output signal,and the filtered signal are utilized to propose an event-triggering mechanism that consists of sensor-to-observer(SO)and observer-to-controller(OC).An event-triggered output feedback control approach is given inside backstepping control,whereby the filter may be employed to circumvent the issue of the virtual control function not being differentiable at the trigger time.It is testified that,according to the Lyapunov stability analysis scheme,all closed-loop signals and the system output are ultimately uniformly constrained by our control method.Finally,the simulation examples are performed to confirm the theoretical findings.展开更多
This paper investigates the problem of dynamic output-feedback control for a class of Lipschitz nonlinear systems.First,a continuous-time controller is constructed and sufficient conditions for stability of the nonlin...This paper investigates the problem of dynamic output-feedback control for a class of Lipschitz nonlinear systems.First,a continuous-time controller is constructed and sufficient conditions for stability of the nonlinear systems are presented.Then,a novel event-triggered mechanism is proposed for the Lipschitz nonlinear systems in which new event-triggered conditions are introduced.Consequently,a closed-loop hybrid system is obtained using the event-triggered control strategy.Sufficient conditions for stability of the closed-loop system are established in the framework of hybrid systems.In addition,an upper bound of a minimum inter-event interval is provided to avoid the Zeno phenomenon.Finally,numerical examples of a neural network system and a genetic regulatory network system are provided to verify the theoretical results and to show the superiority of the proposed method.展开更多
This paper investigates the adaptive stabilization for a class of uncertain PDE-ODE cascaded systems. Remarkably, the PDE subsystem allows unknown control coefficient and spatially varying parameter, and only its one ...This paper investigates the adaptive stabilization for a class of uncertain PDE-ODE cascaded systems. Remarkably, the PDE subsystem allows unknown control coefficient and spatially varying parameter, and only its one boundary value is measurable. This renders the system in question more general and practical, and the control problem more challenging. To solve the problem,an invertible transformation is first introduced to change the system into an observer canonical form,from which a couple of filters are constructed to estimate the unmeasurable states. Then, by adaptive technique and infinite-dimensional backstepping method, an adaptive controller is constructed which guarantees that all states of the resulting closed-loop system are bounded while the original system states converging to zero. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed method.展开更多
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.
基金This work was supported by National Natural Science Foundation of China(NSFC)(No.60374015).
文摘A novel adaptive neural network （NN） output-feedback regulation algorithm for a class of nonlinear time-varying timedelay systems is proposed. Both the designed observer and controller are independent of time delay. Different from the existing results, where the upper bounding functions of time-delay terms are assumed to be known, we only use an NN to compensate for all unknown upper bounding functions without that assumption. The proposed design method is proved to be able to guarantee semi-global uniform ultimate boundedness of all the signals in the closed system, and the system output is proved to converge to a small neighborhood of the origin. The simulation results verify the effectiveness of the control scheme.
基金supported by National Natural Science Foundation of China(61403013)the Aero-Science Foundation of China(2015ZA51009)
文摘In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control(DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.
基金This work was supported by the National Natural Science Foundation of China(No.60304002), and the Science and Technical Development Plan ofShandong Province(No.2004GG4204014).
文摘In this paper, the output tracking control is investigated for a class of nonlinear systems when only output is available for feedback. Based on the multivariable analog of circle criterion, an observer is first introduced. Then, the observer-based output tracking controller is constructively designed by using the integral backstepping approach together with completing square. It is shown that, under relatively mild conditions, all the closed-loop signals are uniformly bounded. Meanwhile the system output asymptotically tracks the desired output. A simulation example is given to illustrate the effectiveness of the theoretical results.
基金the National Natural Science Foundation of China under Grant U22A2043.
文摘This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.
基金supported by the National Natural Science Foundation of China (60804021)the Fundamental Research Funds for the Central Universities (JY10000970001)
文摘An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems.Both the designed observer and controller are free from time delays.Different from the existing results,this paper need not the assumption that the upper bounding functions of time-delay terms are known,and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms,so the designed controller procedure is more simplified.In addition,the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded,and the output regulation error converges to a small residual set around the origin.Two simulation examples are provided to verify the effectiveness of control scheme.
基金supported by the National Natural Science Foundation of China (60804021)
文摘For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic non- linear output-feedback systems. Different from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate for all unknown nonlinear functions so that the controller design is more simplified. Based on stochastic LaSalle theorem, the resulted closed-loop system is proved to be globally asymptotically stable in probability. The simulation results further verify the effectiveness of the control scheme.
基金This project was supported by the National Natural Science Foundation of China(69974017 60274020 60128303)
文摘The back-stepping designs based on confine functions are suggested for the robust output-feedback global stabilization of a class of nonlinear continuous systems; the proposed stabilizer is efficient for the nonlinear continuous systems confined by a bound function, the nonlinearities of the systems may be of varied forms or uncertain; the designed stabilizer is robust means that a class of nonlinear continuous systems can be stabilized by the same output feedback stabilization schemes; numerical simulation examples are given.
基金The work of W.Zheng and Q.Ling was partially supported by the National Natural Science Foundation of China(No.61273112)the National Key Research and Development Project(No.2016YFC0201003).The work of H.Lin was partially supported by the National Science Foundation(Nos.NSF-CNS-1239222,NSF-CNS-1446288,NSF-EECS-1253488).
文摘This paper considers the consensus problem of a group of homogeneous agents.These agents are governed by a general linear system and can only directly measure the output,instead of the state.In order to achieve the consensus goal,each agent estimates its state through a Luenberger observer,exchanges its estimated state with neighbors,and constructs the control input with the estimated states of its own and neighbors.Due to the existence of observation and process noises,only practical consensus,instead of asymptotical consensus,can be achieved in such multi-agent systems.The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents.That performance is closely related to the observation gains of the state observers and the control gains of agents.This paper proposes a method to optimize such performance with respect to the concerned observation and control gains.That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities(LMIs).Solving these LMIs gives some intermediate matrix variables.By perturbing observation and control gains,and the intermediate matrix variables,the original LMIs yield another group of LMIs,which can be solved to provide a descent direction of observation and control gains.Moving along that descent direction,observation and control gains can be improved to yield better performance and work as the starting point of the next iteration.By iteratively repeating this procedure,we can hopefully improve the consensus performance of the concerned multi-agent system.Simulations are done to demonstrate the effectiveness of the proposed method.
基金Supported by National Natural Science Foundation of China(60374002,60674036)the Science and Technical Development Plan of Shandong Province (2004GG4204014)the Program for New Century Excellent Talents in University of China
基金Supported by National Natural Science Foundation of China （60674036）, the Science and Technical Development Plan of Shandong Province （2004GG4204014）, the Program for New Century Excellent Talents in University of China （NCET-07-0513）, the Key Science and Technique Foundation of Ministry of Education of China （108079）, and the Excellent Young and Middle-aged Scientist Award of Shandong Province of China （2007BS01010）
基金Supported by National Natural Science Foundation of P. R. China (60304002)the Science and Technology Development Plan of Shandong Province (2004GG4204014)
文摘The output-feedback stabilization control problem is investigated for a class of nonlinear uncertain systems. Based on the multivariable analog of circle criterion, an observer is designed to estimate the system states and hence the dynamical equations that the estimation error satisfies are derived first. Then, by using integral backstepping approach together with completing square technique, the output-feedback stabilization control is constructively designed such that the closed-loop system is asymptotically stable. Finally, an example is given to illustrate the main results of this paper.
基金Supported by National Natural Science Foundation of China（60774010 10971256） Natural Science Foundation of Jiangsu Province（BK2009083）+1 种基金 Program for Fundamental Research of Natural Sciences in Universities of Jiangsu Province（07KJB510114） Shandong Provincial Natural Science Foundation of China（ZR2009GM008 ZR2009AL014）
基金National Natural Science Foundation of China （60674036, 60974003）, the Natural Science Foundation for Distinguished Young Scholar of Shandong Province of China （JQ200919）, the Program for New Century Excellent Talents in University of China （NCET-07-0513）, the Key Science and Technique Foundation of Ministry of Education of China （108079）, the Excellent Young and Middle-Aged Scientist Award Grant of Shandong Province of China （2007BS01010）
基金Supported by National Natural Science Foundations of China （61325016, 61273084, 61233014）, Natural Science Foundation for Distinguished Young Scholar of Shandong Province of China （JQ200919）, and the Independent Innovation Foundation of Shan- dong University （2012JC014）
基金supported by National Natural Science Foundation of China(Nos.61210011and61203010)National Science Fund for Distinguished Youth Scholars of China(No.60425310)+1 种基金Scientific Research Fund of Hunan Provincial Education Department(No.12B044)Hunan Natural Science Foundation(No.11JJ4059)
文摘This paper deals with the problem of designing a robust discrete output-feedback based repetitive-control system for a class of linear plants with periodic uncertainties. The periodicity of the repetitive-control system is exploited to establish a two-dimensional （2D） model that converts the design problem into a robust stabilization problem for a discrete 2D system. By employing Lyapunov stability theory and the singular-value decomposition of the output matrix, a linear-matrix-inequality （LMI） based stability condition is derived. The condition can be used directly to design the gains of the repetitive controller. Two tuning parameters in the LMI enable the preferential adjustment of control and learning. A numerical example illustrates the design procedure and demonstrates the validity of the method.
基金supported by the National Natural Science Foundation of China(Grant Nos.62176111,62333004,62173172)the Excellent Young Scientists Fund Program(Overseas)the"Xingliao Talent Plan"for young top talents(Grant No.XLYC2203188).
文摘The article addresses the output-feedback control issue for a class of multi-input multi-output(MIMO)uncertain nonlinear systems with multiple event-triggered mechanisms(ETM).Compared to previous event-triggering studies,this paper aims to trigger both the output and filtered signals.Unknown nonlinear dynamics are approximated using fuzzy logic systems(FLSs).Then,a novel kind of state observer has been designed to deal with unmeasurable state problems using the triggered output signal.The sampled estimated state,the triggered output signal,and the filtered signal are utilized to propose an event-triggering mechanism that consists of sensor-to-observer(SO)and observer-to-controller(OC).An event-triggered output feedback control approach is given inside backstepping control,whereby the filter may be employed to circumvent the issue of the virtual control function not being differentiable at the trigger time.It is testified that,according to the Lyapunov stability analysis scheme,all closed-loop signals and the system output are ultimately uniformly constrained by our control method.Finally,the simulation examples are performed to confirm the theoretical findings.
基金supported by the Jiangsu Provincial Natural Science Foundation of China(No.BK20201340)the 333 High-level Talents Training Pro ject of Jiangsu Provincethe China Postdoctoral Science Foundation(No.2018M642160)。
文摘This paper investigates the problem of dynamic output-feedback control for a class of Lipschitz nonlinear systems.First,a continuous-time controller is constructed and sufficient conditions for stability of the nonlinear systems are presented.Then,a novel event-triggered mechanism is proposed for the Lipschitz nonlinear systems in which new event-triggered conditions are introduced.Consequently,a closed-loop hybrid system is obtained using the event-triggered control strategy.Sufficient conditions for stability of the closed-loop system are established in the framework of hybrid systems.In addition,an upper bound of a minimum inter-event interval is provided to avoid the Zeno phenomenon.Finally,numerical examples of a neural network system and a genetic regulatory network system are provided to verify the theoretical results and to show the superiority of the proposed method.
基金supported by the National Natural Science Foundations of China under Grant Nos.61821004,61873146 and 61773332the Special Fund of Postdoctoral Innovation Projects in Shandong Province under Grant No.201703012。
文摘This paper investigates the adaptive stabilization for a class of uncertain PDE-ODE cascaded systems. Remarkably, the PDE subsystem allows unknown control coefficient and spatially varying parameter, and only its one boundary value is measurable. This renders the system in question more general and practical, and the control problem more challenging. To solve the problem,an invertible transformation is first introduced to change the system into an observer canonical form,from which a couple of filters are constructed to estimate the unmeasurable states. Then, by adaptive technique and infinite-dimensional backstepping method, an adaptive controller is constructed which guarantees that all states of the resulting closed-loop system are bounded while the original system states converging to zero. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed method.
