NP-hardness of some linear control design problems

We show that some basic linear control design problems are NP-hard, implying that, unless P=NP, they cannot be solved by polynomial time algorithms. The problems that we consider include simultaneous stabilization by output feedback, stabilization by state or output feedback in the presence of bounds on the elements of the gain matrix, and decentralized control. These results are obtained by first showing that checking the existence of a stable matrix in an interval family of matrices is an NP-hard problem.

[1]  B. Anderson,et al.  Output feedback stabilization and related problems-solution via decision methods , 1975 .

[2]  J. Pearson Linear multivariable control, a geometric approach , 1977 .

[3]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[4]  W. M. Wonham,et al.  Linear Multivariable Control , 1979 .

[5]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[6]  Mathukumalli Vidyasagar,et al.  Control System Synthesis , 1985 .

[7]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[8]  D. Bernstein Some open problems in matrix theory arising in linear systems and control , 1992 .

[9]  Svatopluk Poljak,et al.  Checking robust nonsingularity is NP-hard , 1993, Math. Control. Signals Syst..

[10]  G. Coxson,et al.  Computational complexity of robust stability and regularity in families of linear systems , 1993 .

[11]  Arkadi Nemirovski,et al.  Several NP-hard problems arising in robust stability analysis , 1993, Math. Control. Signals Syst..

[12]  John N. Tsitsiklis,et al.  Complexity theoretic aspects of problems in control theory , 1993 .

[13]  Vincent D. Blondel,et al.  Simultaneous Stabilization Of Linear Systems , 1993 .

[14]  Christopher L. DeMarco,et al.  The computational complexity of approximating the minimal perturbation scaling to achieve instability in an interval matrix , 1994, Math. Control. Signals Syst..

[15]  Marie-Françoise Roy,et al.  On the combinatorial and algebraic complexity of quantifier elimination , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.

[16]  Vincent D. Blondel,et al.  Survey on the State of Systems and Control , 1995, Eur. J. Control.

[17]  Marie-Françoise Roy,et al.  On the combinatorial and algebraic complexity of Quanti erEliminationS , 1994 .

[18]  Herbert S. Wilf,et al.  Algorithms and Complexity , 1994, Lecture Notes in Computer Science.