Analysis of linear‐quadratic optimal control via a hybrid control lens

Abstract Linear‐quadratic regulator (LQR) is a landmark problem in the field of optimal control, which is investigated based on the method of hybrid dynamic system and continuous‐time optimization algorithms. We show that the above‐mentioned hybrid system converges exponentially to the optimal feedback gain with any order, and the solution trajectory is Zeno‐free. Then, the forward‐Euler method is utilized to discretize the hybrid system, and a new algorithm called hybrid dynamics‐based gradient descent (HGD) is proposed that could converge to the optimal controller exponentially.

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Publication Details

Journal
Asian Journal of Control
Published
2024-12-01
DOI
https://doi.org/10.1002/asjc.3551
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Analysis of linear‐quadratic optimal control via a hybrid control lens

Yuan‐Hua Ni, Lechen Feng
Asian Journal of Control
Optimization and Variational Analysis
article

Analysis of linear‐quadratic optimal control via a hybrid control lens

Yuan‐Hua Ni, Lechen Feng
article en

Abstract

Abstract Linear‐quadratic regulator (LQR) is a landmark problem in the field of optimal control, which is investigated based on the method of hybrid dynamic system and continuous‐time optimization algorithms. We show that the above‐mentioned hybrid system converges exponentially to the optimal feedback gain with any order, and the solution trajectory is Zeno‐free. Then, the forward‐Euler method is utilized to discretize the hybrid system, and a new algorithm called hybrid dynamics‐based gradient descent (HGD) is proposed that could converge to the optimal controller exponentially.

Asian Journal of ControlVol. 27(4)
Nankai University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 74%
Optimization and Variational Analysis
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