State and mode feedback control strategy for discrete‐time Markovian jump linear systems with time‐varying controllable mode transition probability matrix

2020 ◽  
Vol 30 (8) ◽  
pp. 3501-3519
Author(s):  
Jin Zhu ◽  
Xinghua Wu ◽  
Chaoxiang Li ◽  
Geir E. Dullerud
Keyword(s):  
Discrete Time ◽  
Control Strategy ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Time Varying ◽  
Mode Transition ◽  
Markovian Jump ◽  
Jump Linear Systems ◽  
Markovian Jump Linear Systems ◽  
Feedback Control Strategy

scholarly journals ℋ∞Model Reduction for Discrete-Time Markovian Jump Systems with Deficient Mode Information

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Yanling Wei ◽  
Mao Wang ◽  
Hamid Reza Karimi ◽  
Nan Wang ◽  
Jianbin Qiu
Keyword(s):  
Model Reduction ◽  
Discrete Time ◽  
Transition Probabilities ◽  
Transition Probability ◽  
Markovian Jump ◽  
Jump Linear Systems ◽  
Markovian Jump Linear Systems ◽  
Transition Probability Matrices ◽  
Probability Matrices ◽  
Jump Systems

This paper investigates the problem ofℋ∞model reduction for a class of discrete-time Markovian jump linear systems (MJLSs) with deficient mode information, which simultaneously involves the exactly known, partially unknown, and uncertain transition probabilities. By fully utilizing the properties of the transition probability matrices, together with the convexification of uncertain domains, a newℋ∞performance analysis criterion for the underlying MJLSs is first derived, and then two approaches, namely, the convex linearisation approach and iterative approach, for theℋ∞model reduction synthesis are proposed. Finally, a simulation example is provided to illustrate the effectiveness of the proposed design methods.

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