In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The ...In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.展开更多
Adaptive control of a flexible beam system preceded by an unknown dead-zonein the driving motor is investigated in state space form. By introducing an important lemma forsimplifying error equation between the flexible...Adaptive control of a flexible beam system preceded by an unknown dead-zonein the driving motor is investigated in state space form. By introducing an important lemma forsimplifying error equation between the flexible beam model and the matching reference model, arobust adaptive control scheme is developed by involving the dead-zone inverse terms. The newadaptive control law ensures global stability of the entire system and achieves desired trackingprecision even when the slopes of the dead-zone are not equal. Simulations performed on a typicalflexible beam system illustrate and clarify the validity of this approach.展开更多
The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adapt...The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.展开更多
基金supported by National Natural Science Foundationof China (No. 60774017 and No. 60874045)
文摘In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.
基金Supported by National Basic Research Program of China （973 Program） （2009CB320604）, National Natural Science Foundation of China （60974043, 60904010）, the Funds for Creative Research Groups of China （60821063）, the 111 Project （B08015）, the Project of Technology Plan of Fujian Province （2009H0033）, and the Project of Technology Plan of Quanzhou （2007G6）
基金This project is supported by National Natural Science Foundation of China (No. 59885002).
文摘Adaptive control of a flexible beam system preceded by an unknown dead-zonein the driving motor is investigated in state space form. By introducing an important lemma forsimplifying error equation between the flexible beam model and the matching reference model, arobust adaptive control scheme is developed by involving the dead-zone inverse terms. The newadaptive control law ensures global stability of the entire system and achieves desired trackingprecision even when the slopes of the dead-zone are not equal. Simulations performed on a typicalflexible beam system illustrate and clarify the validity of this approach.
基金This project was supported by the National Natural Science Foundation of China (60074013)the Foundation of New Era Talent Engineering of Yangzhou University.
文摘The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.
