In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertaintie...In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.展开更多
This paper presents a novel design method for discrete-time repetitive control systems （RCS） based on two-dimensional （2D） discrete-time model. Firstly, the 2D model of an RCS is established by considering both th...This paper presents a novel design method for discrete-time repetitive control systems （RCS） based on two-dimensional （2D） discrete-time model. Firstly, the 2D model of an RCS is established by considering both the control action and the learning action in RCS. Then, through constructing a 2D state feedback controller, the design problem of the RCS is converted to the design problem of a 2D system. Then, using 2D system theory and linear matrix inequality （LMI） method, stability criterion is derived for the system without and with uncertainties, respectively. Parameters of the system can be determined by solving the LMI of the stability criterion. Finally, numerical simulations validate the effectiveness of the proposed method.展开更多
Some typical structural schemes of learning control have been investigated.The schemes involve the pattern recognitionbased learning control,iterative learning control,repetitive learning control,and connectionist lea...Some typical structural schemes of learning control have been investigated.The schemes involve the pattern recognitionbased learning control,iterative learning control,repetitive learning control,and connectionist learning control,etc.This study focuses on the control mechanism and provides a basis for potential applications.Most of the structural schemes have been applied to various control fields.展开更多
A robust adaptive repetitive learning control method is proposed for a class of time-varying nonlinear systems. Nussbaum-gain method is incorporated into the control design to counteract the lack of a priori knowledge...A robust adaptive repetitive learning control method is proposed for a class of time-varying nonlinear systems. Nussbaum-gain method is incorporated into the control design to counteract the lack of a priori knowledge of the control direction which determines the motion direction of the system under any input. It is shown that the system state could converge to the desired trajectory asymptotically along the iteration axis through repetitive learning. Simulation is carried out to show the validity of the proposed control method.展开更多
This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetit...This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.展开更多
An adaptive repetitive control scheme is proposed for trajectory-keeping of satellite formation flying in the leader–follower mode which is described by Lawden equation.The system is parameterised by power series app...An adaptive repetitive control scheme is proposed for trajectory-keeping of satellite formation flying in the leader–follower mode which is described by Lawden equation.The system is parameterised by power series approximation and the unknown timevarying parameters are estimated by adaptive repetitive learning law.Through rigorous analysis by constructing a Lyapunov-like composite energy function(CEF),the stability of the closed-loop system is proved.Finally,a simulation example is provided to illustrate the effectiveness of the control algorithms proposed in this paper.展开更多
基金supported by the Third Level of Hangzhou 131 Young Talent Cultivation Plan Funding2018 Soft Science Research Project of Zhejiang Provincial Science and Technology Department Zhejiang Province Construction and participate in the“The Belt and Road”Technology Innovation Community Path Research(2018C35029)
文摘In this paper, both output-feedback iterative learning control(ILC) and repetitive learning control(RLC) schemes are proposed for trajectory tracking of nonlinear systems with state-dependent time-varying uncertainties. An iterative learning controller, together with a state observer and a fully-saturated learning mechanism, through Lyapunov-like synthesis, is designed to deal with time-varying parametric uncertainties. The estimations for outputs, instead of system outputs themselves, are applied to form the error equation, which helps to establish convergence of the system outputs to the desired ones. This method is then extended to repetitive learning controller design. The boundedness of all the signals in the closed-loop is guaranteed and asymptotic convergence of both the state estimation error and the tracking error is established in both cases of ILC and RLC. Numerical results are presented to verify the effectiveness of the proposed methods.
基金Supported by the Scientific Research Foundation for the Returned 0verseas Chinese Scholars, State Education Ministry, and National Natural Science Foundation of China （60474005）
基金supported by National Natural Science Foundation of China (Nos. 60974045 and 60674016)the Research Foundation of Education Bureau of Hunan Province, China (No. 08C090)
文摘This paper presents a novel design method for discrete-time repetitive control systems （RCS） based on two-dimensional （2D） discrete-time model. Firstly, the 2D model of an RCS is established by considering both the control action and the learning action in RCS. Then, through constructing a 2D state feedback controller, the design problem of the RCS is converted to the design problem of a 2D system. Then, using 2D system theory and linear matrix inequality （LMI） method, stability criterion is derived for the system without and with uncertainties, respectively. Parameters of the system can be determined by solving the LMI of the stability criterion. Finally, numerical simulations validate the effectiveness of the proposed method.
文摘Some typical structural schemes of learning control have been investigated.The schemes involve the pattern recognitionbased learning control,iterative learning control,repetitive learning control,and connectionist learning control,etc.This study focuses on the control mechanism and provides a basis for potential applications.Most of the structural schemes have been applied to various control fields.
基金supported by the National Basic Research Program of China (No. 2012CB316400)the National Science Foundation of China (Nos.60974135, 60525316, 61171034)the Zhejiang Provincial Natural Science Foundation of China (No. R1110443)
文摘A robust adaptive repetitive learning control method is proposed for a class of time-varying nonlinear systems. Nussbaum-gain method is incorporated into the control design to counteract the lack of a priori knowledge of the control direction which determines the motion direction of the system under any input. It is shown that the system state could converge to the desired trajectory asymptotically along the iteration axis through repetitive learning. Simulation is carried out to show the validity of the proposed control method.
基金supported by National Natural Science Foundation of China(Nos.61273070 and 61203092)111 project(No.B12018)
文摘This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multipleoutput discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.
基金This work was supported by National Natural Science Foundation of China under Grant(NSFC number 60705030).
文摘An adaptive repetitive control scheme is proposed for trajectory-keeping of satellite formation flying in the leader–follower mode which is described by Lawden equation.The system is parameterised by power series approximation and the unknown timevarying parameters are estimated by adaptive repetitive learning law.Through rigorous analysis by constructing a Lyapunov-like composite energy function(CEF),the stability of the closed-loop system is proved.Finally,a simulation example is provided to illustrate the effectiveness of the control algorithms proposed in this paper.
