Balance control of a two-wheeled mobile robot

This thesis presents the control of unstable and nonlinear two-wheeled self-balancing robot using LQG and fuzzy logic control methods in Matlab/Simulation. The control purpose is to keep the stability of the system around an equilibrium point while the robot is moving. A linearized mathematical model is described to obtain a linearized state space model in order to develop LQG controller to control the angle and position of the robot. An optimal linear quadratic estimator has been designed to estimate the state variables of the system and has been connected to an optimal full state feedback regulator (LQR). The designed controller has been implemented on the nonlinear dynamics model of the robot. The control algorithm is extended to an intelligent control since fuzzy logic controller is developed to control the angle of the robot. Also the designed controller is implemented on the nonlinear dynamics of the robot in Matlab/Simulink. The simulation results obtained in Matlab/Simulink show that the proposed controllers are able to achieve the self-balancing of the robot while the wheels keep moving. Key Words: Two-wheeled self-balancing robot, Linear quadratic regulator, Linear quadratic gaussian, Fuzzy logic control