A survey of computational complexity results in systems and control

被引:502
作者
Blondel, VD [1 ]
Tsitsiklis, JN
机构
[1] Catholic Univ Louvain, Dept Engn Math, Ctr Syst Engn & Appl Mech, B-1348 Louvain, Belgium
[2] MIT, Informat & Decis Syst Lab, Cambridge, MA 02139 USA
关键词
control; discrete-event systems; discrete-time systems; hybrid systems; Markov decision processes; mathematical systems theory; neural networks; nonlinear systems; time-varying systems; turing machines;
D O I
10.1016/S0005-1098(00)00050-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The purpose of this paper is twofold: (a) to provide a tutorial introduction to some key concepts from the theory of computational complexity, highlighting their relevance to systems and control theory, and (b) to survey the relatively recent research activity lying at the interface between these fields. We begin with a brief introduction to models of computation, the concepts of undecidability, polynomial-time algorithms, NP-completeness, and the implications of intractability results. We then survey a number of problems that arise in systems and control theory, some of them classical, some of them related to current research. We discuss them from the point of view of computational complexity and also point out many open problems. In particular, we consider problems related to stability or stabilizability of linear systems with parametric uncertainty, robust control, time-varying linear systems, nonlinear and hybrid systems, and stochastic optimal control. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:1249 / 1274
页数:26
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