Title
Event-triggered single-network ADP method for constrained optimal tracking control of continuous-time non-linear systems.
Abstract
This paper investigates the optimal tracking control problem (OTCP) for continuous-time non-linear systems with input constraints. A novel event-triggered single-network adaptive dynamic programming (ADP) method is proposed to obtain the solution of constrained OTCP. By constructing an augmented system and introducing a novel discounted non-quadratic cost function, an event-triggered constrained tracking Hamilton–Jacobi–Bellman equation is formulated. Then, only a critic neural network (NN) is employed to learn the optimal value function and further obtain the optimal tracking controller, which enables the architecture of ADP implementation to be simpler. And a novel NN weights updating law is constructed, by which the restriction of initial admissible control is removed. Based on the Lyapunov theory, the convergence of critic NN weights and the stability of closed-loop system are demonstrated. The derived optimal tracking controller is updated only at the event-triggered instants decided by the designed event-triggered condition. Therefore, the communication burden can be reduced effectively. Finally, two simulation examples are given to verify the effectiveness of proposed method.
Year
DOI
Venue
2019
10.1016/j.amc.2019.01.066
Applied Mathematics and Computation
Keywords
Field
DocType
Adaptive dynamic programming,Tracking control,Input constraints,Event-triggered
Convergence (routing),Dynamic programming,Lyapunov function,Mathematical optimization,Control theory,Nonlinear system,Bellman equation,Event triggered,Artificial neural network,Mathematics
Journal
Volume
ISSN
Citations 
352
0096-3003
1
PageRank 
References 
Authors
0.35
28
5
Name
Order
Citations
PageRank
Lili Cui1905.03
Xiang-Peng Xie286054.50
Xiao-Wei Wang359659.78
Luo Yan-Hong45710.00
Jingbo Liu511218.56