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A new iterative algorithm for solving H ∞ control problem of continuous‐time Markovian jumping linear systems based on online implementation
Author(s) -
Song Jun,
He Shuping,
Ding Zhengtao,
Liu Fei
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3531
Subject(s) - computer science , convergence (economics) , mathematical optimization , decoupling (probability) , linear system , iterative method , transformation (genetics) , algebraic riccati equation , algorithm , linear programming , dynamic programming , markov decision process , set (abstract data type) , markov process , mathematics , riccati equation , mathematical analysis , biochemistry , chemistry , statistics , programming language , control engineering , engineering , economics , gene , differential equation , economic growth
Summary A new online iterative algorithm for solving the H ∞ control problem of continuous‐time Markovian jumping linear systems is developed. For comparison, an available offline iterative algorithm for converging to the solution of the H ∞ control problem is firstly proposed. Based on the offline iterative algorithm and a new online decoupling technique named subsystems transformation method, a set of linear subsystems, which implementation in parallel, are obtained. By means of the adaptive dynamic programming technique, the two‐player zero‐sum game with the coupled game algebraic Riccati equation is solved online thereafter. The convergence of the novel policy iteration algorithm is also established. At last, simulation results have illustrated the effectiveness and applicability of these two methods. Copyright © 2016 John Wiley & Sons, Ltd.