6533b838fe1ef96bd12a5198

RESEARCH PRODUCT

A simplified predictive control of constrained Markov jump system with mixed uncertainties

Hamid Reza KarimiYanyan YinYanqing Liu

subject

Mathematical optimizationArticle Subjectlcsh:MathematicsApplied MathematicsPolytopeState (functional analysis)Analysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Set (abstract data type)Model predictive controlPolyhedronControl theoryTrajectoryInvariant (mathematics)AnalysisMathematicsMarkov jump

description

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/475808 Open Access 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.

yearjournalcountryeditionlanguage
2014-01-01
http://hdl.handle.net/11250/273671