Study On Performance Improvement Of Variable Structure Control For Two-wheeled Self-balancing Vehicle

The two-wheeled self-balancing vehicle is a special kind of wheeled mobile robot and a complex system in nature, its dynamic equations are multi-variable, nonlinear, strong coupling, parameter uncertainty and so on. Not only the environment in which the vehicle moves is complicated, but also the task needs to complete is arduous. Therefore, the two-wheeled self-balancing vehicle is an ideal platform for studying variety of control methods. At present, the fuzzy control, optimal control and PID control are commonly used to control the two-wheeled self-balancing vehicle, but the variable structure control is rarely used. In this paper, we use the Variable Structure Controller to control this vehicle system. The work can be listed below.Firstly, though analyzing and studying the model of two-wheeled self-balancing system in home and abroad, we gave the vehicle's nonlinear model.Secondly, after comparing the condition number of controllability matrix about linear mode obtained around the balanced point based on Taylor series linearized model, fuzzy weighted linearized model and the feedback linearized mode respectively, we got that the feedback linearized model is very approximate to that original nonlinear model.Finally, according to the variable structure control theory, we know that the robustness is contradict to chattering. In order to impair the chattering effectively and remain the robustness of the sliding-mode in the variable structure control at the same time, the dynamic pseud-sliding mode control with disturbance compensation term based on feedback linearized model is designed, which not only effectively impairs the chattering, but also guarantees the robustness of the system. The results of simulation and experiment demonstrate that this controller is more effective in control the two-wheeled self-balancing vehicle. After simulation, we also got that when there is perturbation in the system ,the controller based on fuzzy weighted linearized model is easily to make the nonlinear system stable than the controller based on Taylor series linearized model.