Closed-Loop RBF-PID Control Method for Position and Attitude Control of Stewart Platform

Stewart platform has the characteristics of high nonlinearity and strong coupling, and conventional control method can not eliminate assembly and theoretical model errors. In this paper, the closed-loop control strategy is used to realize the position and attitude control of Stewart platform. For the closed-loop controller, the online tuning method of controller parameters based on RBF neural network is studied. The simulation results show that the control strategy is better than the conventional control strategy, and the tracking performance and control precision are significantly improved.