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

机译:事件触发的自适应控制设计,具有宏观微型复合定位级的规定性能

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This article investigates the rapid vibration reduction problem for macro-micro composite positioning stage (MMCPS), which is of great engineering significance for microelectronics manufacturing. The MMCPS is modeled as a nonstrict 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 semiglobally uniformly ultimately bounded. Finally, the simulation results are conducted to illustrate the effectiveness of the control algorithm.
机译:本文研究了宏观微型复合定位阶段(MMCP)的快速减振问题,对微电子制造具有巨大的工程意义。 MMCP被建模为非防盗反馈互连的非线性系统。 基于BackStepping技术和径向基函数神经网络,开发了一种具有规定性能的事件触发的自适应控制方案。 通过设计性能函数和坐标转换,获得了预期的状态收敛速率和精度。 采用相对阈值事件触发机制来降低控制输入的更新频率。 事实证明,闭环系统的所有信号都是半球形均匀的最终限定的。 最后,进行仿真结果以说明控制算法的有效性。

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