Decision-control mechanism for Markovian jump linear systems with Gaussian noise

Jin Zhu, Yewen Wang, Wanqing Xie, Geir E. Dullerud

Research output: Contribution to journalArticlepeer-review


Summary This paper investigates the decision-control mechanism for Markovian jump linear systems with Gaussian noise. The mechanism here consists of two parts: decision to govern the mode transition rate matrix and output-feedback controller to govern system state. Motivated by this, a joint index is put forward to evaluate system performance, which is a combination of traditional jump linear quadratic Gaussian cost and additional decision cost because extra expenses will be taken for adopting decision to mode transition rate matrix. For the minimization of joint index, the designing of optimal decision-control pair is deduced to the seeking of optimal decision. Meanwhile, the optimal decision can be obtained via an iterative with its convergence proved. Numerical examples illustrate the validity of the proposed mechanism.

Original languageEnglish (US)
Pages (from-to)381-393
Number of pages13
JournalOptimal Control Applications and Methods
Issue number2
StatePublished - Mar 1 2016


  • Gaussian noise
  • Markovian jump linear systems
  • decision-control mechanism
  • joint index

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Control and Optimization
  • Applied Mathematics


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