Stable iterative adaptive dynamic programming algorithm with approximation errors for discrete-time nonlinear systems

In this paper, a novel iterative adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. When the iterative control law and iterative performance index function in each iteration cannot be accurately obtained,...

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Vydáno v:	Neural computing & applications Ročník 24; číslo 6; s. 1355 - 1367
Hlavní autoři:	Wei, Qinglai, Liu, Derong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.05.2014 Springer
Témata:	Algorithmics. Computability. Computer arithmetics Applied sciences Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer science; control theory; systems Control system synthesis Control theory. Systems Data Mining and Knowledge Discovery Exact sciences and technology Image Processing and Computer Vision Learning and adaptive systems Optimal control Original Article Probability and Statistics in Computer Science Theoretical computing Approximate dynamic programming Adaptive dynamic programming Neural networks Nonlinear systems Optimal control Adaptive critic designs Policy On line Stability Reinforcement learning Control program Non linear control Error bound Iterative method Neural network Non linear system Indirect method Discrete time Approximation error Off line Infinite horizon Dynamic programming Optimal control (mathematics)
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
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