Research Of Control Algorithm Of Two-Wheeled Self-Balancing Robot

Two-wheeled self-balancing robot based on the inverted pendulum model belongs to the category of the wheeled robots and combines with the idea of autonomous moving. The robot is small in mechanism and can make a flexible motion. So it is fit for tasks in narrow and dangerous space and has a wide foreground both in civilian and military application. The instability of balancing robot systems will also be an excellent test bed for control theory experimentation.The controller developing processes involved in balancing a two-wheeled autonomous robot is mainly discussed in this paper. The state-space equation is obtained through the mathematical model which is established by the analysis of kinematics and dynamics. In order to obtain an optimal estimate of the tilt angle and angle velocity, an indirect Kalman filter configuration combining a rate gyroscope sensor and an accelerometer is implemented. Because of the extreme nonlinearity of the two-wheeled self-balancing robot, application feasibility of nonlinear system control strategy based on linear approximation method, exact linearization and intelligent control have been investigated. According to robustness, balancing performance and environment adaptability, Robust tracking control, Linear Quadratic Regulator and Fuzzy model reference learning control are implemented to the velocity controller. Utilizing Control Lyapunov Function, the position control and trajectory control law are designed for the robot.Using MATLAB and Simulink, Simulation results are provided to show the efficacy of the Kalman filter and controllers. Also, multi-sensor data fusion, balancing control,robustness control and velocity tracking experiments are conducted to ensure the validity and efficacy.