Abstract
In this paper, the optimal regulation and tracking control of affine nonlinear continuous-time systems with known dynamics is undertaken using a novel single online approximator (SOL)-Based scheme. the SOLA-Based adaptive approach is designed to learn the infinite horizon continuous time Hamilton-Jacobi-Bellman (HJB) equation and its corresponding optimal control input. a novel parameter tuning algorithm is derived which not only ensures the optimal cost (HJB) function and control input are achieved, but also ensures the system states remain bounded during the online learning process. Lyapunov techniques show that all signals are uniformly ultimately bounded (UUB) and the approximated control signal approaches the optimal control input with small, bounded error. in the absence of OLA reconstruction errors, asymptotic convergence to the optimal control is shown. Simulation results illustrate the effectiveness of the approach. © 2010 AACC.
Recommended Citation
T. Dierks and S. Jagannathan, "Optimal Control of Affine Nonlinear Continuous-time Systems," Proceedings of the 2010 American Control Conference, ACC 2010, pp. 1568 - 1573, article no. 5531586, Institute of Electrical and Electronics Engineers, Jan 2010.
The definitive version is available at https://doi.org/10.1109/acc.2010.5531586
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Hamilton-Jacobi-Bellman; Lyapunov stability; Online approximators; Online nonlinear optimal control
International Standard Book Number (ISBN)
978-142447426-4
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2010
