Paper Info
Title
Data-Driven Finite-Horizon Optimal Control For Linear Time-Varying Discrete-Time Systems
Abstract
This paper presents a data-driven method to obtain an approximate solution of the finite-horizon optimal control problem for linear time-varying discrete-time systems. Firstly, a finite-horizon Policy Iteration method for linear time-varying discrete-time systems is proposed. Then, a data-driven off-policy Policy Iteration algorithm is derived to find approximate optimal controllers when the system dynamics is unknown. Under mild conditions, the proposed data-driven off-policy algorithm converges to the optimal solution. Finally, the effectiveness of the derived method is validated by a numerical example.
Year
DOI
Venue
2018
10.1109/CDC.2018.8619347
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
Field
DocType
ISSN
Mathematical optimization,Data-driven,Optimal control,Computer science,Iterative method,System dynamics,Discrete time and continuous time,Finite horizon,Time complexity,Approximate solution
Conference
0743-1546
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Bo Pang15795451.00
Tao Bian2746.15
Zhong-Ping Jiang34595351.78