Balance control of two-wheeled self-balancing robot based on Linear Quadratic Regulator and Neural Network

Abstract

Two-wheeled self-balancing robot is a kind of unstable, nonlinear, strong coupling system. On the basis of analyzing the method of Linear Quadratic Regulator(LQR) and PID-BP-RBF, this paper proposed a new balance control method based on LQR and Neural Network(NN)(LQR-NN).In this method, the balance controller is designed as a LQR controller contained a neural network inside. The LQR's optimal parameters are used to initialize the neural network, which would make the network have the optimum initial values and converge fast. The new method can overcome the inaccuracy modeling because of system linearization based on LQR, and also has the self-turning mechanism without great computation load which the NN method brings. Experiments show that the balance controller based on LQR-NN has better balancing control to the robot and also improved the system's robustness significantly.