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
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
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 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 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.
