Sparse feedback structures for control of civil systems
Sparse feedback structures for control of civil systems
复制标题
用于控制民用系统的稀疏反馈结构
DOI：
10.1002/stc.1847
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发表时间：
2016
影响因子：
5.4
通讯作者：
Lauren E. Linderman
中科院分区：
文献类型：
--
作者：
Reuben D. Verdoljak;Lauren E. Linderman
现代结构控制系统使用集中式有线传感器反馈，根据响应测量结果施加反作用力。然而，集中式系统可能对传感器故障、控制器故障和传感器链路的可靠性敏感。最近的研究无线控制系统鼓励分散控制方法，以克服无线结构控制的挑战，包括限制所需的无线通信和相关的低采样率和控制系统中的时间延迟。分散控制提供了多个独立控制器和测量反馈的小子集的额外优点。以前的分散式结构控制算法，无论是Ad‐Hoc还是启发式，都在设计过程中强制执行空间稀疏模式，这是先验假设的。因此，在设计中没有考虑最优反馈结构。这项工作探讨了一个分散的最优LQR设计算法的反馈增益的稀疏性被纳入目标函数。在5层和20层控制基准结构上，将该控制方法与以前的分散控制技术进行了比较，这些基准结构都装有主动或半主动系统。此外，稀疏性和控制要求进行了比较与集中式设计，以了解稀疏反馈系统的整体性能。最佳稀疏反馈设计提供了性能、测量反馈和控制工作的最佳平衡。此外，在20层结构的降阶模型中，识别的反馈结构不容易先验识别，突出了该反馈框架中特定测量的重要性。版权所有© 2016约翰威利父子有限公司.
Modern structural control systems use centralized, wired sensor feedback to impart counter forces based on measurement of the response. However, centralized systems can be sensitive to sensor failure, controller failure, and the reliability of sensor links. The recent study of wireless control systems has encouraged decentralized control approaches to overcome wireless structural control challenges, including limiting the wireless communication required and the associated slow sampling rate and time delays in the control system. Decentralized control offers the additional advantages of multiple independent controllers and small subsets of measurement feedback. Previous decentralized structural control algorithms, both Ad‐Hoc and Heuristic, enforce a spatial sparsity pattern during the design, which is assumed a priori. Therefore, the optimal feedback structure is not considered in the design. This work explores a decentralized optimal LQR design algorithm where the sparsity of the feedback gain is incorporated into the objective function. The control approach is compared with previous decentralized control techniques on 5‐ and 20‐story control benchmark structures fitted with active or semi‐active systems. Additionally, the sparsity and control requirements are compared with centralized designs to gain insight on the overall performance of sparse feedback systems. The optimal sparse feedback design offers the best balance of performance, measurement feedback, and control effort. Additionally, the feedback structure identified is not easily identifiable a priori in the reduced order model of the 20‐story structure, highlighting the significance of particular measurements in this feedback framework. Copyright © 2016 John Wiley & Sons, Ltd.