Asymptotic tracking control scheme for mechanical systems with external disturbances and friction

In this paper, a novel control scheme is proposed for the tracking problem of mechanical systems in the presence of external vibrations and friction. An acclerometer is installed on the load frame in the mechanical systems to detect the external vibrations. Then a neural network (NN) compensator with accelerometer signal as its input is adopted for feedforward compensation of external vibrations. Another NN is employed to compensate for the unknown system dynamics thereby compensate for friction. To eliminate the residual reconstruction error coming from NN approximation, the robust integral of the sign of the error (RISE) feedback term is integrated into the control scheme. A Lyapunov stability analysis is performed to show that the proposed control scheme can be used to yield a semi-global asymptotic tracking result rather than uniformly ultimately bounded (UUB) results derived by typical NN-based controllers. In particular, exact models of the plant, external disturbances and the accelerometer are not needed. A comparative study on system performance is conducted on a two-link robot manipulator between the proposed control scheme and the main conventional control methods for showing satisfactory tracking performance of the proposed control scheme.