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Event-based model-free adaptive control for discrete-time non-linear processes

机译:离散时间非线性过程的基于事件的无模型自适应控制

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摘要

In this study, a novel event-based model-free adaptive control (MFAC) algorithm for discrete-time non-linear systems is presented. Different from the traditional MFAC scheme which calculates the control signal at fixed sampling instants, an event-based sampling scheme is given to calculate the new control signal only when the input/output (I/O) data sufficiently changes. The event-triggered MFAC can obviously reduce the computational load and network communication. The closed-loop system is proven to be ultimately bounded by using the Lyapunov technique. Finally, the simulation examples indicate the effectiveness and applicability of the proposed event-trigger model-free adaptive control algorithm.
机译:在这项研究中,提出了一种新颖的基于事件的离散时间非线性系统的无模型自适应控制(MFAC)算法。与在固定采样时刻计算控制信号的传统MFAC方案不同,仅在输入/输出(I / O)数据充分变化时,才提供基于事件的采样方案来计算新的控制信号。事件触发的MFAC可以明显减少计算量和网络通信。事实证明,使用李雅普诺夫(Lyapunov)技术可以最终控制闭环系统。最后,仿真算例表明了所提出的无事件触发模型的自适应控制算法的有效性和适用性。

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