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Backstepping Sliding Mode Control with FWNN for Strict Output Feedback Non-Smooth Nonlinear Dynamic System

Seong-Ik Han and Jang-Myung Lee*
International Journal of Control, Automation, and Systems, vol. 11, no. 2, pp.398-409, 2013

Abstract : An output feedback backstepping sliding mode control scheme was developed for precision position-ing of a strict single-input and single-output (SISO) non-smooth nonlinear dynamic system that could compensate for deadzone, dynamic friction, uncertainty and estimations of immeasurable states. An adaptive fuzzy wavelet neural networks (FWNNs) technique was used to provide improved ap-proximation ability to the system uncertainty. The adaptive laws were derived for application to esti-mate the deadzone and friction parameters using recursive backstepping controller design procedures. In addition, the sliding mode control method was also combined to enforce the robustness of the output feedback backstepping controller against disturbance. The Lyapunov stability theorem was used to prove stability of the proposed control system. The usefulness of the proposed control system was verified by simulations and experiments on a robot manipulator in the presence of a deadzone and friction in the actuator.

Keyword : Backstepping sliding mode control, fuzzy wavelet neural networks, non-smooth nonlinearity, robot manipulator, strict output feedback SISO dynamic system.

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