Abstract: Ball and plate system is a typical two-input two-output system. Aiming at the problems of slow response and serious shocks in RBF-PID control algorithm. The Lagrange equation is used to model the ball and plate system under the condition of ignoring the interference factors. Radical Basis Function (RBF) neural network is used to identify the discrete model of ball and plate system on line and realize adaptive control. On this basis, the Levenberg-Marquardt (LM) algorithm replaces the gradient descent method to set the control parameters. The LM_RBF-PID controller is designed and compared with the RBF-PID controller in terms of step signal response and square wave signal response. Finally, a square trajectory tracking experiment is completed in the ball and plate system. The experimental results show that proposed algorithm improves trajectory tracking control accuracy, and it can ensure the stability and convergence of the tracking control in the ball and plate system.

Key words: ball and plate system, Levenberg-Marquardt algorithm, neural network, Matlab