Adaptive Sliding Mode Control for Three-Wheel Omnidirectional Mobile Robot

Abstract

Nowadays, mobile robots are applied to many types of jobs in different industries such as industry, logistics, service and some dangerous fields that replace humans, such as mine detection, oil and gas exploitation, chemical production, and weapons. Therefore, there is more and more research on mobile robot control. This paper proposes a new control method that is to use a sliding mode controller (SMC) combined with adaptive law based on radial basis function neural network (RBFNN) for a three-wheeled omnidirectional mobile robot (TWOMR). In the process of working, the robot will be affected by external disturbances and model uncertainty, so the neural network is used to approximate these components. The system is proven stable based on Lyapunov's theory. The system simulation results show that the proposed controller meets the desired quality criteria.