Noise Tolerance of Online Self-Tuning Mechanism for Model-Free Vibration Controller Based on a Virtual Controlled Object
Noise Tolerance of Online Self-Tuning Mechanism for Model-Free Vibration Controller Based on a Virtual Controlled Object
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DOI：
10.1109/iccma56665.2022.10011456
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Ansei Yonezawa;Heisei Yonezawa;I. Kajiwara
中科院分区：
文献类型：
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作者：
Ansei Yonezawa;Heisei Yonezawa;I. Kajiwara
本研究提出了一种自适应自整定振动控制方案。该方法无需受控对象建模即可构建，且自整定方案具有较强的抗噪能力。通过在执行器模型和实际受控对象之间引入虚拟受控对象（VCO）（单自由度系统），导出设计无模型控制器的状态方程。使用状态方程设计了基于 VCO 的无模型线性二次调节器 (VCO-LQR)。基于 VCO 的自适应控制是通过将 VCO-LQR 与基于测量输出和同时扰动随机逼近 (SPSA) 的在线自调节机制相结合而建立的。由于基于 VCO 的控制器设计以及基于 SPSA 和测量的自整定方案，基于 VCO 和 SPSA 的自适应振动抑制方法非常简单。此外，这种自调整机制具有很强的噪声容忍度，因为 SPSA 可以由噪声损失函数测量驱动。通过振动控制仿真证明了自调节方案的阻尼性能和噪声容限。
This study presents an adaptive self-tuning vibration control scheme. This method can be constructed without controlled object modelling and the self-tuning scheme has strong noise tolerance. A state equation to design a model-free controller is derived by introducing a virtual controlled object (VCO), which is a single-degree-of-freedom system, between an actuator model and an actual controlled object. A VCO-based model-free linear quadratic regulator (VCO-LQR) is designed using the state equation. The VCO-based adaptive control is established by combining the VCO-LQR with an online self-tuning mechanism based on measured outputs and the simultaneous perturbation stochastic approximation (SPSA). The VCO- and the SPSA-based adaptive vibration suppression method is extremely simple due to the VCO-based controller design and the SPSA- and measurement-based self-tuning scheme. Moreover, this self-tuning mechanism has strong noise tolerance because the SPSA can be driven by noisy loss function measurements. The damping performance and noise tolerance of the self-tuning scheme are demonstrated via vibration control simulations.