Open AccessApproximate optimal control for a class of nonlinear discrete-time systems with saturating actuators
Author(s) -
Yanhong Luo,
Huaguang Zhang
Publication year - 2008
Publication title -
progress in natural science materials international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.864
H-Index - 63
eISSN - 1745-5391
pISSN - 1002-0071
DOI - 10.1016/j.pnsc.2008.03.006
Subject(s) - optimal control , control theory (sociology) , nonlinear system , convergence (economics) , dynamic programming , controller (irrigation) , actuator , mathematical optimization , bellman equation , discrete time and continuous time , heuristic , function (biology) , mathematics , computer science , class (philosophy) , control (management) , artificial intelligence , evolutionary biology , quantum mechanics , physics , economic growth , biology , agronomy , statistics , economics
In this paper, we solve the approximate optimal control problem for a class of nonlinear discrete-time systems with saturating actu- ators via greedy iterative Heuristic Dynamic Programming (GI-HDP) algorithm. In order to deal with the saturating problem of actu- ators, a novel nonquadratic functional is developed. Based on the nonquadratic functional, the GI-HDP algorithm is introduced to obtain the optimal saturated controller with a rigorous convergence analysis. For facilitating the implementation of the iterative algo- rithm, three neural networks are used to approximate the value function, compute the optimal control policy and model the unknown plant, respectively. An example is given to demonstrate the validity of the proposed optimal control scheme. 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.
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