Robust adaptive neural networks sliding mode control for three-freedom robot
Abstract
This paper presents an algorithm to design a robust adaptive controller for strictly parameter feedback plant with function uncertainty. The control algorithm is synthesized on sliding mode control principle. The function uncertainty of the plant is approximated by a two layer radial basis function neural networks, the weigh coefficients are frained on-line. The proposed controller is used to control a three-freedom robot model. The simulation results show the advances and the application ability in practice of the proposed control algorithm.