Abstract and Applied Analysis

A Simplified Predictive Control of Constrained Markov Jump System with Mixed Uncertainties

Yanyan Yin, Yanqing Liu, and Hamid R. Karimi

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A simplified model predictive control algorithm is designed for discrete-time Markov jump systems with mixed uncertainties. The mixed uncertainties include model polytope uncertainty and partly unknown transition probability. The simplified algorithm involves finite steps. Firstly, in the previous steps, a simplified mode-dependent predictive controller is presented to drive the state to the neighbor area around the origin. Then the trajectory of states is driven as expected to the origin by the final-step mode-independent predictive controller. The computational burden is dramatically cut down and thus it costs less time but has the acceptable dynamic performance. Furthermore, the polyhedron invariant set is utilized to enlarge the initial feasible area. The numerical example is provided to illustrate the efficiency of the developed results.

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Abstr. Appl. Anal., Volume 2014, Special Issue (2013), Article ID 475808, 7 pages.

First available in Project Euclid: 6 October 2014

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Yin, Yanyan; Liu, Yanqing; Karimi, Hamid R. A Simplified Predictive Control of Constrained Markov Jump System with Mixed Uncertainties. Abstr. Appl. Anal. 2014, Special Issue (2013), Article ID 475808, 7 pages. doi:10.1155/2014/475808. https://projecteuclid.org/euclid.aaa/1412605763

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