A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems
Abstract
This paper addresses problems on the structural design of control systems taking explicitly into consideration the possible application to large-scale systems. We provide an efficient and unified framework to solve the following major minimization problems: (i) selection of the minimum number of manipulated/measured variables to achieve structural controllability/observability of the system, and (ii) selection of the minimum number of feedback interconnections between measured and manipulated variables such that the closed-loop system has no structurally fixed modes. Contrary to what would be expected, we show that it is possible to obtain a global solution for each of the aforementioned minimization problems using polynomial complexity algorithms in the number of the state variables of the system. In addition, we provide several new graph-theoretic characterizations of structural systems concepts, which, in turn, enable us to characterize all possible solutions to the above problems.
Keywords
Cite
@article{arxiv.1309.5868,
title = {A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems},
author = {Sergio Pequito and Soummya Kar and A. Pedro Aguiar},
journal= {arXiv preprint arXiv:1309.5868},
year = {2014}
}
Comments
Software for implementing the input-output and control configuration selection algorithms presented in the paper can be downloaded from http://www.mathworks.com/matlabcentral/fileexchange/46848-a-framework-for-structural-input-output-and-control-configuration-selection-in-large-scale-systems