Adaptive dynamic surface control for a class of strict-feedback nonlinear systems with unknown backlash-like hysteresis

In this paper, we investigate the control design for a class of strict-feedback nonlinear systems preceded by unknown backlash-like hysteresis. Using the characteristics of backlash-like hysteresis, adaptive dynamic surface control (DSC) is developed without constructing a hysteresis inverse. The explosion of complexity in traditional backstepping design is avoided by utilizing DSC. Function uncertainties are compensated for using neural networks due to their universal approximation capabilities. Through Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Simulation results are provided to illustrate the performance of the proposed approach.