Optimal fuzzy control of a two-wheel mobile robot equipped with a control moment gyroscope (CMG) stabilizer: Simulation and experiment

Abstract This paper presents the modeling, development, and control of a two-wheel mobile robot equipped with a control moment gyroscope (CMG) stabilizer. The study begins by employing a specific method and selecting alternative generalized coordinates to extract the nonholonomic constraint equations of the robot motion. Subsequently, the dynamic governing equations are obtained using the constrained Lagrangian approach. The balance of the robot is controlled in two states: while stationary and while tracking a certain trajectory. Two distinct control approaches are examined. First, the conventional Feedback Linearization Method is applied, and its performance is illustrated. Next, a Fuzzy control is designed and proposed as an optimal and intelligent controller. The superiority of the fuzzy controller over the conventional method is then demonstrated. The accuracy and reliability of the designed controllers are investigated using MATLAB simulations. The controller's performance is evaluated in three different scenarios: stabilizing the robot when deflected from the vertical position, tracking paths while maintaining balance for two reference trajectories, and developing an experimental bicycle robot equipped with a CMG. In these simulations, the robot balance controller and the robot trajectory tracking controller effectively control the balance and path tracking of the robot. Following the simulations, the bicycle robot equipped with a CMG is developed experimentally. The results obtained from the experimental study are presented and discussed to validate the effectiveness of the proposed controllers. Both simulation and experimental findings confirm the proper performance of the proposed intelligent Fuzzy controller in balancing the robot in stationary states and tracking desired trajectories.