Adaptive Neural-Network Control of Mobile Robot Formations Including Actuator Dynamics

Abstract

For the formation control problem of multiple nonholonomic mobile robots with actuator and formation dynamics, this paper propsed a new control strategy that integrated kinematic controller with input voltages controller of actuator. This control law was designed by backstepping technique based on formation control structure of leader-follower. The RBFNN was adopted to achieve on-line estimation for the dynamics nonlinear uncertain part for follower and leader robots. The adaptive robust controller was adopted to compensate modeling errors of neural network. This strategy not only solved the problem of parameters and non-parameter uncertainties of mobile robots, but also ensured the desired trajectory tracking of robot formation in the case of maintaining formation. The stability and convergence of the control system were proved by using the Lyapunov theory. The simulation results showed the effectiveness of this proposed method.