Paper Info
Title
An Iterative Data-Driven Linear Quadratic Method to Solve Nonlinear Discrete-Time Tracking Problems
Abstract
The objective of this article is to introduce a novel data-driven iterative linear quadratic (LQ) control method for solving a class of nonlinear optimal tracking problems. Specifically, an algorithm is proposed to approximate the Q-factors arising from LQ stochastic optimal tracking problems. This algorithm is then coupled with iterative LQ-methods for determining local solutions to nonlinear opt...
Year
DOI
Venue
2021
10.1109/TAC.2021.3056398
IEEE Transactions on Automatic Control
Keywords
DocType
Volume
Optimal control,Heuristic algorithms,Dynamic programming,Approximation algorithms,Q-factor,Stochastic processes,Mathematical model
Journal
66
Issue
ISSN
Citations 
11
0018-9286
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Possieri, C.16223.78
Gian Paolo Incremona2709.40
Giuseppe Carlo Calafiore340933.87
A. Ferrara4953126.03