Event-Triggered Adaptive Control Design With Prescribed Performance for Macro-Micro Composite Positioning Stage

This article investigates the rapid vibration reduction problem for macro-micro composite positioning stage, which is of great engineering significance for microelectronics manufacturing. The macro-micro composite positioning stage is modeled as a non-strict feedback interconnected nonlinear system. Based on backstepping technique and radial basis function neural networks, an event-triggered adaptive control scheme with prescribed performance is developed. By designing performance function and coordinate transformation, the expected state convergence rate and precision are obtained. The relative threshold event-triggering mechanism is adopted to decrease the update frequency of control input. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded. Finally, the simulation results are conducted to illustrate the effectiveness of the control algorithm.