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'Convexifying' Linear Matrix Inequality Methods for Integrating Structure and Control Design

机译:用于集成结构和控制设计的“凸化”线性矩阵不等式方法

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摘要

This paper presents a methodology in the linear matrix inequality (LMI) framework to jointly optimize the linear control law and the linear parameters in the structure. The method allows the mass matrix to contain free parameters, while employing LMI methods. The paper solves a structure design problem which bounds the covariance of selected outputs, such as interstory drifts and their velocities, in the presence of random excitations. In fact, the method simultaneously designs the structure and the controller, yielding a hybrid control. The proposed method also allows one to guarantee bounds on the peak response in the presence of bounded energy excitations. With minor modifications, the method can also guarantee bounds on the H_(infinity) performance and many other convex performance criteria. The nonconvex problem is approximated by a convex one by adding a certain function to make the constraint convex. This "convexifying" function is updated with each iteration until the added convexifying function disappears at a saddle point of the nonconvex problem. This is a new contribution to both control theory and structure design.
机译:该文提出了一种线性矩阵不等式(LMI)框架中联合优化线性控制律和结构中线性参数的方法。该方法允许质量矩阵包含自由参数,同时采用LMI方法。本文解决了一个结构设计问题,该问题在存在随机激励的情况下限制了所选输出的协方差,例如层间漂移及其速度。事实上,该方法同时设计了结构和控制器,从而产生了混合控制。所提出的方法还允许在存在有界能量激励的情况下保证峰值响应的边界。通过稍作修改,该方法还可以保证H_(无穷大)性能和许多其他凸性能标准的边界。非凸问题通过添加某个函数使约束凸化来近似于凸问题。这个“凸化”函数在每次迭代时都会更新,直到添加的凸化函数在非凸问题的鞍点消失。这是对控制理论和结构设计的新贡献。

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