The Implementation of Wheeled Robot Using Adaptive Output Recurrent CMAC

Abstract

In this study, an adaptive output recurrent cerebellar model articulation controller (AORCMAC) is investigated to control the two-wheeled robot. The main purpose is to develop a self-dynamic balancing and motion control strategy. The proposed AORCMAC has superior capability to the conventional cerebellar model articulation controller in efficient learning mechanism and dynamic response. The dynamic gradient descent method is adopted to online adjust the AORCMAC parameters. Therefore, AORCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism and dynamic response. Finally, the effectiveness of the proposed control system is verified by the experiments of the two-wheeled robot standing control. Experimental results show that the the two-wheeled robot can stand upright stably with uncertainty disturbance by using the proposed AORCMAC.