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In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot hand joints. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuno control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.