Based On Adaptive Fuzzy Sliding Mode Robot Control

A main concern of robotic applications is to find an effective controller t o achieve accurate tracking of desired motions. Several existing controlmeihod s can be used in the case that the manipulator parameters and the load are k nown in advance. However, in the presence of parameter uncertainties, the m any of these control techniques fail to track the desired motion satisfactorily, or quickly become unstable, so that the performance of the control systems a re degaraded. The tracking controls for multi-joint rigid robot manipulators wi th parametric(structure) and nonparametric uncertainties are studied in this thes is. By applying the schemes proposed in it, the stabilities of the control syste ms and the the boundedness of the control signals can be ensured so that so me problems in previous controllers are alleviated or avoided. The simulation results sufficiently verify the validity of the control schemes. The thesis mainly consists of three parts.In the first part, by introducing fuzzy logic to the sliding mode control, the control signals can be softened so that the chattering phenomenon ina co nventional sliding mode control system is alleviated. The stability of the fuzzy control system and the boundedness of the tracking error and control signals a re ensured by Lyapunov method.In the second part, based on sliding mode control theory and the approx imation capability of fuzzy systems, a new scheme of adaptive fuzzy sliding mode control system is proposed. The control architecture employs fuzzy syst ems to compensate adaptively for plant uncertainties. The stability of the fuzz y control system and the convergence of the tracking errors are ensured using the Lyaponov theory.In the third part, the design of the controller is based on sliding mode control theory and the approximation capability of fuzzy systems. The adaptivelaw is choosed and the stability of the fuzzy control system , the convergen...