Adaptive dynamic surface control with sliding mode control and RWNN for robust positioning of a linear motion stage

Abstract Ball-screw-driven system provides high precision and long stroke range for positioning and tracking control of a linear stage. Friction and backlash nonlinearities in this system act often the main obstacles for high precision control. It is difficult to achieve effective compensation of these types of nonlinearities by traditional linear control methodology without the aid of a proper compensation schemes. Here, we present an adaptive dynamic surface control scheme combined with sliding mode control to compensate for friction and backlash nonlinearities in a linear stage motion system. The adaptive laws of the recurrent wavelet neural networks and friction estimation are derived to approximate and compensate for the backlash and friction nonlinearities. The boundedness and convergence of the closed-loop system are guaranteed from a Lyapunov stability analysis. The performance of the proposed control scheme was verified through simulations and experiments on the ball-screw-driven linear stage.

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