Infinite-horizon optimal control problems for nonlinear systems
File(s)CDC_tutorial_optimal_control.pdf (677.66 KB)
Accepted version
Author(s)
Sassano, Mario
Mylvaganam, Thulasi
Astolfi, Alessandro
Type
Conference Paper
Abstract
Infinite-horizon optimal control problems for non-linear systems are studied and discussed. First, we thoroughlyrevisit the formulation of the underlying dynamic optimisation problem together with the classical results providing itssolution. Then, we consider two alternative methods to con-struct solutions (or approximations there of) of such problems, developed in recent years, that provide theoretical insights as well as computational benefits. While the considered methods are mostly based on tools borrowed from the theories of Dynamic Programming and Pontryagin’s Minimum Principles, or a combination of the two, the proposed control design strategies yield innovative, systematic and constructive methods to provide exact or approximate solutions of nonlinear optimal control problems. Interestingly, similar ideas can be extended also to linear and nonlinear differential games, namely dynamic optimisation problems involving several decision-makers. Due their advantages in terms of computational complexity, the considered methods have found several applications. An example ofthis is provided, through the consideration of the multi-agent collision avoidance problem, for which both simulations and experimental results are provided.
Date Issued
2022-02-01
Date Acceptance
2021-07-31
Citation
2022, pp.1721-1721
Publisher
IEEE
Start Page
1721
End Page
1721
Copyright Statement
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Commission of the European Communities
Identifier
https://ieeexplore.ieee.org/document/9683321
Grant Number
739551
Source
IEEE Conference on Decision and Control (CDC 2021)
Subjects
Science & Technology
Technology
Automation & Control Systems
Engineering, Electrical & Electronic
Engineering
GAME APPROACH
Publication Status
Published
Start Date
2021-12-13
Finish Date
2021-12-17
Coverage Spatial
Austin, Texas, USA
Date Publish Online
2022-02-01