An adaptive backstepping-based non-singular termi- nal sliding mode （NTSM） control method is proposed for a class of uncertain nonlinear systems in the parameteric-strict feedback form. The adaptive control law is c...An adaptive backstepping-based non-singular termi- nal sliding mode （NTSM） control method is proposed for a class of uncertain nonlinear systems in the parameteric-strict feedback form. The adaptive control law is combined with the first n - 1 steps of the backstepping method to estimate the unknown pa- rameters of the system. In the nth step, an NTSM control strategy is utilized to drive the last state of the system to converge in a finite time. Furthermore, the derivate estimator is used to obtain the derivates of the states of the error system; the higher-order non-singular terminal sliding mode control （HONTSMC） law is de- signed to eliminate the chattering and make the system robust to both matched and unmatched uncertainties. Compared to the adaptive backstepping-based linear sliding mode control method （LSMC）, the proposed method improves the convergence rate and the steady-state tracking accuracy of the system, and makes the control signal smoother. Finally, the compared simulation results are presented to validate the method.展开更多
基金supported by the Natural Science Foundation of Heilongjiang Province(E201426)
文摘An adaptive backstepping-based non-singular termi- nal sliding mode （NTSM） control method is proposed for a class of uncertain nonlinear systems in the parameteric-strict feedback form. The adaptive control law is combined with the first n - 1 steps of the backstepping method to estimate the unknown pa- rameters of the system. In the nth step, an NTSM control strategy is utilized to drive the last state of the system to converge in a finite time. Furthermore, the derivate estimator is used to obtain the derivates of the states of the error system; the higher-order non-singular terminal sliding mode control （HONTSMC） law is de- signed to eliminate the chattering and make the system robust to both matched and unmatched uncertainties. Compared to the adaptive backstepping-based linear sliding mode control method （LSMC）, the proposed method improves the convergence rate and the steady-state tracking accuracy of the system, and makes the control signal smoother. Finally, the compared simulation results are presented to validate the method.
