Controller architectures: Tradeoffs between performance and structure

被引:68
作者
Jovanovic, Mihailo R. [1 ]
Dhingra, Neil K. [1 ]
机构
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
基金
美国国家科学基金会;
关键词
Controller architecture; Convex optimization; Distributed control; Networks of dynamical systems; Non-smooth optimization; Performance vs. complexity; Regularization; Sparsity-promoting optimal control; Structured optimal control; Structure identification; SPATIALLY INVARIANT-SYSTEMS; H-2-OPTIMAL DECENTRALIZED CONTROL; DISTRIBUTED CONTROL DESIGN; STATE-SPACE SOLUTION; CONVEX CHARACTERIZATION; MULTIAGENT SYSTEMS; LEADER SELECTION; POSITIVE SYSTEMS; NETWORKS; CONTROLLABILITY;
D O I
10.1016/j.ejcon.2016.05.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This review article describes the design of static controllers that achieve an optimal tradeoff between closed-loop performance and controller structure. Our methodology consists of two steps. First, we identify controller structure by incorporating regularization functions into the optimal control problem and, second, we optimize the controller over the identified structure. For large-scale networks of dynamical systems, the desired structural property is captured by limited information exchange between physical and controller layers and the regularization term penalizes the number of communication links. Although structured optimal control problems are, in general, nonconvex, we identify classes of convex problems that arise in the design of symmetric systems, undirected consensus and synchronization networks, optimal selection of sensors and actuators, and decentralized control of positive systems. Examples of consensus networks, drug therapy design, sensor selection in flexible wing aircrafts, and optimal wide-area control of power systems are provided to demonstrate the effectiveness of the framework. (C) 2016 European Control Association. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:76 / 91
页数:16
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