Feedback linearization based controller design for two-wheeled balance vehicles

In this thesis, a two-wheeled self-balancing vehicle was controlled. The mathematical models of the vehicle were created as dynamic and state space equations with the energy-based Lagrangian method. The two-wheeled balance vehicle was designed in 3D in the SolidWorks drawing environment and transferred to the Matlab/Simulink environment. The vehicle was connected to the controller prepared in the Matlab/Simulink environment and controlled in 3D environment. In addition, a 2D simulation of the inverted pendulum system has been carried out in order to monitor the tilt and position. In the control of the vehicle, besides its position, the balance angle, left/right turning angle and speed were checked. The amount of energy that needs to be transferred to the motors during these inspections is given by including the friction energies. Full state feedback linearization, pole placement and linear quadratic regulator control methods are used for the control of the two-wheeled balance vehicle. Comparisons of the control methods used were made by giving graphics of changes in position, balance angle, speed and motor torque. In the comparisons, it was seen that the feedback linearization method gave better performance than pole placement and linear quadratic regulator under the same conditions. The feedback linearization control method was faster than the others in taking the two-wheeled self-balancing vehicle to the desired location, and the deterioration in the balance angle was not much. It has been observed that the linear quadratic regulator has low performance as well as low energy use.