Trajectory tracking controller design for manipulator with variable loads
In this paper,a neural network adaptive switching control strategy based on the average dwell time is proposed for uncertain rigid manipulator system with variable loads.In this proposal,the rigid manipulator system holding different loads is treated as a switched system,which is divided into several subsystems according to different loads,and then different sub controllers are designed for each subsystem based on the average dwell time principle.In every subsystem,the RBF neural network is utilized for approaching to the system structural parameters to avoid the dependence of the controller on accurate system model.Meanwhile,the RBF neural network is employed to design the robust compensation term to suppress the influence of lumped disturbance of the system.Then,the uniform final boundedness of trajectory tracking error is verified by multi-Lyapunov function method.Finally,the simulation results show that the proposed algorithm can not only achieve the high-precision tracking of the manipulator with variable loads,but effectively eliminate the chattering of input torque.
switching controllerrobotic manipulatorneural networkaverage dwell timeadaptive control
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