2012Kongzhi yu jueceRequires access

Adaptive backstepping high-order terminal sliding mode control for uncertain nonlinear systems

Jianbo Hu

Open publisher page 6 citations

Abstract

A neural network adaptive backstepping high-order terminal sliding mode control scheme is proposed for a class of uncertain nonlinear systems with mismatched uncertainties.At the first 1 steps,neural networks are employed to approximate the unknown nonlinear functions and the dynamic surface control is combined with backstepping design technique to design the virtual controller,so that the explosion of complexity in traditional backstepping design is avoided and mismatched uncertainties are restrained perfectly.In the-th step,the high-order sliding mode control law is designed by combining with the non-singular terminal sliding mode to eliminate the chattering and make the system robust to both matched and mismatched uncertainties.By theoretical analysis,all the states in the closed loop systems are guaranteed to be semi-globally uniformly ultimately bounded.Finally,the simulation results show the effectiveness of the proposed method.

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What this paper is about

A neural network adaptive backstepping high-order terminal sliding mode control scheme is proposed for a class of uncertain nonlinear systems with mismatched uncertainties.At the first 1 steps,neural networks are employed to approximate the unknown nonlinear functions and the dynamic surface control is combined with backstepping design technique to design the virtual controller,so that the explosion of complexity in traditional backstepping design is avoided and mismatched uncertainties are restrained perfectly.In the-th step,the high-order sliding mode control law is designed by combining with the non-singular terminal sliding mode to eliminate the chattering and make the system robust to both matched and mismatched uncertainties.By theoretical analysis,all the states in the closed loop systems are guaranteed to be semi-globally uniformly ultimately bounded.Finally,the simulation results show the effectiveness of the proposed method.

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Available abstract

A neural network adaptive backstepping high-order terminal sliding mode control scheme is proposed for a class of uncertain nonlinear systems with mismatched uncertainties.At the first 1 steps,neural networks are employed to approximate the unknown nonlinear functions and the dynamic surface control is combined with backstepping design technique to design the virtual controller,so that the explosion of complexity in traditional backstepping design is avoided and mismatched uncertainties are restrained perfectly.In the-th step,the high-order sliding mode control law is designed by combining with the non-singular terminal sliding mode to eliminate the chattering and make the system robust to both matched and mismatched uncertainties.By theoretical analysis,all the states in the closed loop systems are guaranteed to be semi-globally uniformly ultimately bounded.Finally,the simulation results show the effectiveness of the proposed method.

Key concepts: Backstepping, Control theory (sociology), Nonlinear system, Sliding mode control, Terminal sliding mode, Controller (irrigation), Bounded function, Strict-feedback form

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