Adaptive fuzzy control of mobile robots with full-state constraints and unknown longitudinal slipping

Motion control of wheeled mobile robots with state constraints under slipping condition faces many difficulties, such as unmeasurable velocities, non-holonomic kinematic model, and unknown disturbances. Aiming at these problems, an adaptive fuzzy controller is proposed in this paper. Firstly, a fuzzy state observer is developed to estimate the velocity and compensate the unknown complex system model. Then, a output vector is designed to convert the position constraint to output constraints, and a Barrier Lypunov Function is constructed to ensure the motion constraint. Moreover, a simpler longitudinal slipping model that allows handling of longitudinal sliding more conveniently is further designed. The stability of the closed-loop system is analyzed by the Lyapunov theorem. Finally, simulation and experiment verify the effectiveness and practicality of the method under the longitudinal slipping situation, reflecting the suppression effect on tracking errors.