An adaptive critic neural network for motion control of a wheeled mobile robot

In this paper, we propose a new application of the adaptive critic methodology for the feedback control of wheeled mobile robots, based on a critic signal provided by a neural network (NN). The adaptive critic architecture uses a high-level supervisory NN adaptive critic element (ACE), to generate the reinforcement signal to optimise the associative search element (ASE), which is applied to approximate the non-linear functions of the mobile robot. The proposed tracking controller is derived from Lyapunov stability theory and can guarantee tracking performance and stability. A series of computer simulations have been used to emulate the performance of the proposed solution for a wheeled mobile robot.