Title :
Finding the optimal H∞ controller for stochastic Markovian jumping systems by using parallel Kleinman iteration algorithm
Author :
Shuping He ; Jun Song
Author_Institution :
Sch. of Electr. Eng. & Autom., Anhui Univ., Hefei, China
Abstract :
Two computation iterative algorithm are studied to solve the coupled game algebraic Riccati equation (CGARE) associated with the optimal H∞ control problems for a class of Markovian jumping linear systems (MJLSs). The two iterative algorithms are based on the framework of Kleinman iteration algorithm. At first, the direct parallel Kleinman iteration algorithm is proposed and the convergence of the iterative algorithm is established. Then, we introduce a more general iterative algorithm (called generalized parallel Kleinman iteration algorithm) with four different cases. Finally, a numerical example has been provided to demonstrate the effectiveness of the proposed algorithms.
Keywords :
H∞ control; Riccati equations; game theory; iterative methods; linear systems; stochastic systems; CGARE; MJLS; Markovian jumping linear system; coupled game algebraic Riccati equation; generalized parallel Kleinman iteration algorithm; iterative algorithm; optimal H∞ controller; parallel Kleinman iteration algorithm; stochastic Markovian jumping system; Accuracy; Approximation algorithms; Convergence; Iterative methods; Optimal control; Riccati equations; Coupled Game Algebraic Riccati Equation; H∞ Control; Iteration Algorithm; Markovian Jumping Linear Systems;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053045