Actuator Scheduling for Linear Systems: A Convex Relaxation Approach

Junjie Jiao, Dipankar Maity, John S. Baras, Sandra Hirche

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this letter, we investigate the problem of actuator scheduling for networked control systems. Given a stochastic linear system with a number of actuators, we consider the case that one actuator is activated at each time. This problem is combinatorial in nature and NP-Hard to solve. We propose a convex relaxation to the actuator scheduling problem, and use the relaxed solution as a reference to design an algorithm for solving the original scheduling problem. Using dynamic programming arguments, we provide a suboptimality bound of our proposed algorithm. Furthermore, we show that our framework can be extended to incorporate multiple actuator scheduling at each time and actuation costs. A simulation example is provided, which shows that our proposed method outperforms a random selection approach and a greedy selection approach.

Original languageEnglish
Pages (from-to)7-12
Number of pages6
JournalIEEE Control Systems Letters
Volume7
DOIs
StatePublished - 2023

Keywords

  • Actuator scheduling
  • LQG control

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