T-S Recurrent Fuzzy Network Controller for Two-axis Motion Control System

In this paper, a T-S recurrent fuzzy network (TSRFN) control system is proposed to control the position of the mover of x-y table, which is composed of two permanent-magnet linear synchronous motors (PMLSM). The proposed TSRFN combines the merits of self-constructing fuzzy neural network (SCFNN), T-S fuzzy inference mechanism, and recurrent neural network (RNN). The structure and the parameter learning phases were preformed concurrently and online in the TSRFN. Moreover, to improve the control performance in reference contours tracking, the motions at x-axis and y-axis were controlled separately. Simulation results show that the robustness to parameter variations, external disturbances, cross-coupled interference is effective and yield superior performance.