Stabilization of Markov jump linear systems using quantized state feedback

N Xiao, L Xie, M Fu - Automatica, 2010 - Elsevier
N Xiao, L Xie, M Fu
Automatica, 2010Elsevier
This paper addresses the stabilization problem for single-input Markov jump linear systems
via mode-dependent quantized state feedback. Given a measure of quantization
coarseness, a mode-dependent logarithmic quantizer and a mode-dependent linear state
feedback law can achieve optimal coarseness for mean square quadratic stabilization of a
Markov jump linear system, similar to existing results for linear time-invariant systems. The
sector bound approach is shown to be non-conservative in investigating the corresponding …
This paper addresses the stabilization problem for single-input Markov jump linear systems via mode-dependent quantized state feedback. Given a measure of quantization coarseness, a mode-dependent logarithmic quantizer and a mode-dependent linear state feedback law can achieve optimal coarseness for mean square quadratic stabilization of a Markov jump linear system, similar to existing results for linear time-invariant systems. The sector bound approach is shown to be non-conservative in investigating the corresponding quantized state feedback problem, and then a method of optimal quantizer/controller design in terms of linear matrix inequalities is presented. Moreover, when the mode process is not observed by the controller and quantizer, a mode estimation algorithm obtained by maximizing a certain probability criterion is given. Finally, an application to networked control systems further demonstrates the usefulness of the results.
Elsevier
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