Algorithm Design and Convergence Analysis of Iterative Adaptive Dynamic Programming

Bao Sheng Yang; Bao Sheng  Yang; Li Li Chen

doi:10.4028/www.scientific.net/AMM.336-338.852

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 336-338Algorithm Design and Convergence Analysis of...

Algorithm Design and Convergence Analysis of Iterative Adaptive Dynamic Programming

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 336-338)

Pages:

852-855

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.336-338.852

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Online since:

July 2013

Authors:

Bao Sheng Yang, Bao Sheng Yang, Li Li Chen

Keywords:

Iterative Adaptive Dynamic Programming, Neural Network (NN), Optimal Control, Time Delay

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