DocumentCode
624709
Title
Near-optimal control for continuous-time nonlinear systems with control constraints using on-line ADP
Author
Chunbin Qin ; Huaguang Zhang ; Yanhong Luo
Author_Institution
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2013
fDate
9-11 June 2013
Firstpage
754
Lastpage
759
Abstract
In this paper, an on-line adaptive dynamic programming (ADP) algorithm is presented to solve the optimal control problem for continuous-time nonlinear systems with control constraints. First, a suitable non-quadratic performance function is introduced to confront control constraints, and then we present an on-line ADP algorithm in which dynamic programming techniques and neural networks are used to solve the optimal control problem for nonlinear systems with control constraints, which is completely different with the traditional ADP algorithm using off-line training, and the corresponding convergence proof is given. Finally, a simulation examples is given to demonstrate the convergence and feasibility of the proposed algorithm.
Keywords
adaptive control; continuous time systems; convergence; dynamic programming; neurocontrollers; nonlinear control systems; optimal control; continuous-time nonlinear system; control constraint; convergence proof; near-optimal control; neural network; nonquadratic performance function; offline training; online ADP algorithm; online adaptive dynamic programming; optimal control problem; Artificial neural networks; Convergence; Equations; Heuristic algorithms; Nonlinear systems; Optimal control; adaptive dynamic programming; control constraint; neural network; nonlinear system;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4673-6248-1
Type
conf
DOI
10.1109/ICICIP.2013.6568173
Filename
6568173
Link To Document