Algorithm Design and Convergence Analysis of Iterative Adaptive Dynamic Programming

Time delays are tremendous difficulties to system stability analysis and controller design, and often cause system instability or even lead to the deterioration of the system performance. The optimal control law is solved for a class of nonlinear discrete affine systems with multiple time delays. Th...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 336-338; pp. 852 - 855
Main Authors Yang, Bao Sheng, Chen, Li Li
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.07.2013
Subjects
Time Delay
Optimal Control
Iterative Adaptive Dynamic Programming
Neural Network (NN)
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Summary:Time delays are tremendous difficulties to system stability analysis and controller design, and often cause system instability or even lead to the deterioration of the system performance. The optimal control law is solved for a class of nonlinear discrete affine systems with multiple time delays. The systems HJB equation of optimal control is solved by adaptive dynamic iterative algorithm and minimized system performance index function, given the convergence proof of the algorithm. Neural networks are adopted to realize iterative algorithm for optimal control law of time delay systems. The simulation results show that the adaptive dynamic programming can solve for the optimal control of delay nonlinear systems, make the system to achieve stability.
Bibliography:Selected, peer reviewed papers from the 2013 2nd International Conference on Measurement, Instrumentation and Automation (ICMIA 2013), April 23-24, 2013, Guilin, China
ISBN:9783037857519
303785751X
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.336-338.852