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Feedback control of linear systems with optimal sensor and actuator selection

机译:具有最佳传感器和执行器选择的线性系统的反馈控制

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This article demonstrates a combined H-infinity feedback control design for linear time-invariant and linear parameter-varying systems and optimal sensors and actuator selection. The combined design problem is systematically constructed as a mixed Boolean semidefinite programming optimization problem. We impose Big-M reformulations to the non-deterministic polynomial-time-hard coupled problem to be solved as a convex optimization problem using the branch and bound algorithm. The combined design of dynamic output feedback control along with optimal actuator selection for a linear time-invariant seismic rejection controller design serves as an application for validation by simulation. In addition, active vibration control of a smart composite plate along with optimal sensor and actuator selection validates the developed approach for linear parameter-varying controller synthesis. On comparing this approach with exhaustive search, it is observed that mixed Boolean semidefinite programming approaches have faster computation time, and comparing with the iterative reweighted l(1) norm algorithm and mixed Boolean semidefinite programming using outer approximations, mixed Boolean semidefinite programming yields a global solution.
机译:本文介绍了线性时不变和线性参数变化系统的组合H∞反馈控制设计,以及最佳传感器和执行器的选择。将组合设计问题系统地构造为一个混合布尔半定规划优化问题。我们使用分支定界算法将非确定性多项式时间硬耦合问题作为凸优化问题求解,并对其进行了大M重构。动态输出反馈控制与最佳执行器选择的组合设计用于线性时不变抗震控制器设计,作为仿真验证的应用。此外,智能复合材料板的振动主动控制以及最佳传感器和执行器选择验证了所开发的线性参数变化控制器综合方法。通过与穷举搜索方法的比较,发现混合布尔半定规划方法具有更快的计算时间,并且与迭代加权l(1)范数算法和使用外部近似的混合布尔半定规划相比,混合布尔半定规划产生了一个全局解。

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