Adaptive Back-stepping Control of Servo Systems With Asymmetric Dead Zone

In this paper, an adaptive back-stepping control scheme based on the command filter is proposed for the servo system with current constraints and non-symmetric dead zone. First, a novel system transformation scheme is designed to transform the servo system with current constraints into the equivalent “unconstrained”. A security boundary is incorporated into the designed strategy to restrict the activation state of the constraint mechanism. Second, the asymmetric dead zone nonlinearities can be represented into a parameterized form by using a continuous piecewise linear neural network (CPLNN). Moreover, an adaptive law with guaranteed convergence is used to online update the CPLNN weights so as to derive the dead zone characteristic parameters and then compensate for the asymmetric dead zone. Then, the command filter is introduced into the back-stepping control strategy to avoid the complexity explosion. The stability analysis of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness and feasibility of the proposed control scheme are validated through the real-time experiments on a permanent magnet synchronous motor (PMSM) platform.