Passivity analysis and passification for uncertain signal processing systems
Passivity analysis and passification for uncertain signal processing systems
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DOI：
10.1109/78.709527
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发表时间：
1998-09
期刊：
影响因子：
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通讯作者：
Lihua Xie;M. Fu;Huaizhong Li
中科院分区：
文献类型：
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作者：
Lihua Xie;M. Fu;Huaizhong Li
无源分析问题在许多信号处理系统中都有重要的应用，如数字量化器、决策反馈均衡器、数字和模拟滤波器。同样重要的是钝化问题，需要为给定的系统设计一个补偿器，使其变为无源。本文考虑了一类涉及不确定参数、时滞、量化误差和未建模高阶动力学的大系统的这两个问题。通过使用称为积分二次约束（iqc）的通用工具表征这些和许多其他类型的不确定性，我们提出了鲁棒无源分析和鲁棒无源化问题的解决方案。更具体地说，对于分析问题，我们确定给定的不确定系统是否对满足iqc的所有允许不确定性都是被动的。类似地，对于鲁棒钝化问题，我们关心的是找到一个环路变换，使得不确定信号处理系统的特定部分对于所有允许的不确定性都成为无源。根据一个或多个线性矩阵不等式的可行性给出了解，这些解可以有效地求解。
The problem of passivity analysis finds important applications in many signal processing systems such as digital quantizers, decision feedback equalizers, and digital and analog filters. Equally important is the problem of passification, where a compensator needs to be designed for a given system to become passive. This paper considers these two problems for a large class of systems that involve uncertain parameters, time delays, quantization errors, and unmodeled high-order dynamics. By characterizing these and many other types of uncertainty using a general tool called integral quadratic constraints (IQCs), we present solutions to the problems of robust passivity analysis and robust passification. More specifically, for the analysis problem, we determine if a given uncertain system is passive for all admissible uncertainty satisfying the IQCs. Similarly, for the problem of robust passification, we are concerned with finding a loop transformation such that a particular part of the uncertain signal processing system becomes passive for all admissible uncertainty. The solutions are given in terms of the feasibility of one or more linear matrix inequalities (LMIs), which can be solved efficiently.