Sliding mode control based on RBF neural network for parallel machine tool

Abstract

The hydraulic control system, an important composition of parallel machine tool, is a high order, nonlinear, parameter uncertain system, which seriously affects the dynamic performance of a machine tool, so it is very difficult to gain good performance with traditional control methods. The sliding mode control method based on RBF neural network is proposed in this paper. From the simulation results we can obtain that the proposed method is better than the traditional sliding model control method. Moreover, the result validates the proposed method of Hydraulic system for parallel machine tool and also provides the theoretical and experimental basis.