Modified dynamic surface approach with bias torque for multi-motor servomechanism

This paper presents a modified neural dynamic surface control (DSC) with an adaptive bias torque for the multi-motor servomechanism (MMS) with backlash, friction and other disturbances. By introducing a continuous hybrid differentiator to replace the first-order filter in each step, a modified DSC is developed to improve the load tracking precision of MMS. However, when the MMS enters the backlash band, only DSC cannot guarantee the load tracking performance. Thus, an adaptive bias torque is firstly proposed based on the prescribed performance function technique to compensate the backlash nonlinearity and guarantee the load tracking performance of MMS. In addition, the unknown dynamics including the friction and other disturbances are approximated by using wavelet echo state networks where the weights are all updated online. By means of Lyapunov stability theory, the semi-globally uniformly ultimately bounded (SGUUB) property of all signals in the closed-loop system is proved. Finally, simulations and experimental results based on a four-motor servomechanism are presented to show the effectiveness of the proposed approach.