DocumentCode :
2728190
Title :
Optimal control design based on reinforcement learning for a class of nonlinear distributed systems
Author :
Zhen He ; Yanbin Liu
Author_Institution :
Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear :
2013
fDate :
12-14 June 2013
Firstpage :
384
Lastpage :
389
Abstract :
This paper proposes an optimal control scheme for a class of non-affine nonlinear distributed systems. The research is conducted for a tethered parafoil system. The reference inputs are optimized by reinforcement learning method for two optimization goals respectively. A dynamic model approximation method is introduced to approximate the non-affine nonlinear terms. The tracking controller is designed and the stability analysis is given. The methodology is demonstrated by simulations.
Keywords :
control system synthesis; learning (artificial intelligence); nonlinear systems; optimal control; stability; dynamic model approximation; nonaffine nonlinear distributed system; nonaffine nonlinear term; optimal control design; optimization goal; reinforcement learning; stability analysis; tethered parafoil system; tracking controller; Aerodynamics; Approximation methods; Equations; Learning (artificial intelligence); Mathematical model; Nonlinear systems; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Automation (ICCA), 2013 10th IEEE International Conference on
Conference_Location :
Hangzhou
ISSN :
1948-3449
Print_ISBN :
978-1-4673-4707-5
Type :
conf
DOI :
10.1109/ICCA.2013.6565092
Filename :
6565092
Link To Document :
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