Based on the nolinear kinematic model of automatic guided vehicles, an adaptive Backstepping method is
used to design a controller for the kinematic control of automatic guided vehicles with parameter uncertainties. The
convergence of the tracking errors of automatic guided vehicles is proved by using the Lyapunov stability theory. The
tracking differentiator is adopted to acquire the derivatives of virtual control and input signal without noise. Therefore,
the Backstepping implementation is simplified significantly. Furthermore, the control parameters for adaptive controller are
trained by evolutionary programming. Moreover, the simulation results show that the proposed method greatly compensates
the effects of parameter perturbation and improves the system tracking accuracy and robustness in comparison with traditional
PID control laws.