DocumentCode :
493361
Title :
Constrained optimal control of affine nonlinear discrete-time systems using GHJB method
Author :
Cui, Lili ; Zhang, Huaguang ; Liu, Derong ; Kim, Yongsu
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
fYear :
2009
fDate :
March 30 2009-April 2 2009
Firstpage :
16
Lastpage :
21
Abstract :
The infinite-horizon optimal control problem of nonlinear discrete-time systems with actuator saturation is considered in this paper. In order to deal with actuator saturation, a novel nonquadratic functional is introduced, and the constrained generalized Hamilton-Jacobi-Bellman (GHJB) equation and Hamilton-Jacobi-Bellman (HJB) equation for nonlinear discrete-time systems are derived in terms of non-quadratic functionals. The optimal saturated controller is obtained by a novel iterative algorithm based on the constrained GHJB equation, and a convergence proof is presented, where a neural network is used to approximate the value function. Finally, a nearly optimal saturated controller is obtained. The effectiveness of this algorithm is demonstrated by a numerical example.
Keywords :
discrete time systems; infinite horizon; iterative methods; neurocontrollers; nonlinear control systems; optimal control; actuator saturation; affine nonlinear discrete-time systems; constrained Generalized Hamilton-Jacobi-Bellman equation; constrained optimal control; infinite-horizon optimal control problem; iterative algorithm; neural network; nonquadratic functional; Actuators; Continuous time systems; Control systems; Convergence; Iterative algorithms; Nonlinear control systems; Nonlinear equations; Optimal control; Riccati equations; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL '09. IEEE Symposium on
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-4244-2761-1
Type :
conf
DOI :
10.1109/ADPRL.2009.4927520
Filename :
4927520
Link To Document :
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