| 引用本文: | 方昱斌,朱晓锦,高志远,张小兵.多输入多输出微振动系统的混合鲁棒自适应控制[J].控制理论与应用,2024,41(9):1559~1568.[点击复制] |
| FANG Yu-bin,ZHU Xiao-jin,GAO Zhi-yuan,ZHANG Xiao-bing.Hybrid robust adaptive control for multiple-input multiple-output micro-vibration system[J].Control Theory and Technology,2024,41(9):1559~1568.[点击复制] |
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| 多输入多输出微振动系统的混合鲁棒自适应控制 |
| Hybrid robust adaptive control for multiple-input multiple-output micro-vibration system |
| 摘要点击 3003 全文点击 56 投稿时间：2022-04-16 修订日期：2024-07-06 |
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| DOI编号 10.7641/CTA.2023.20282 |
| 2024,41(9):1559-1568 |
| 中文关键词 混合自适应控制 多输入多输出 Q参数化 振动控制 鲁棒自适应 |
| 英文关键词 hybrid adaptive control multiple-input multiple-output Q parameterization vibration control robust adaptive |
| 基金项目 中国博士后科学基金资助项目(2021M691598), 国家自然科学基金面上项目(52175101)资助. |
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| 中文摘要 |
| Q参数化方法在结构振动自适应控制领域的应用中体现出明显优势. 本文针对多输入多输出(MIMO)结构振动主动控制系统, 利用Q参数化方法的优势, 基于无限冲激响应(IIR)滤波器, 提出了一种结合前馈控制与反馈控制的MIMO混合鲁棒自适应控制方法. 同时, 给出前馈, 反馈MIMO鲁棒自适应控制方法的详细推导过程, 给出混合MIMO鲁棒自适应控制方法的推导和稳定性, 收敛性分析. 在此基础上, 通过构建三自由度微振动主动振动控制实验系统, 针对单频窄带和双频窄带扰动展开了对比实验分析, 相关的实验结果验证了本文所提出MIMO混合鲁棒自适应控制方法的可行性和有效性. |
| 英文摘要 |
| In recent years, Q parameterization method has reflected significant advantages in the application of vibration adaptive control. For the multiple input multiple output (MIMO) active vibration control system, a MIMO hybrid robust adaptive vibration control method based unlimited pulse response infinite impulse response (IIR) filter is presented in this paper. This hybrid control method takes advantage of the Q parametrization of the feedback controller and feedforward controller. The deducing process of the feedforward MIMO robust adaptive control method and feedback MIMO robust adaptive control method are illustrated in detail. And based the deducing process of hybrid MIMO robust adaptive control method, it’s stability and convergence are analyzed. A 3-degree of freedom real time micro-vibration control experimental platform is constructed. Comparison with sine disturbance and double sine disturbance are provided. Experimental results confirm the feasibility and effectiveness of the proposed algorithm. |
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