Article
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Online Inverse Optimal Control for Time-Varying Cost Weights
Version 1
: Received: 19 December 2023 / Approved: 19 December 2023 / Online: 20 December 2023 (12:15:31 CET)
A peer-reviewed article of this Preprint also exists.
Cao, S.; Luo, Z.; Quan, C. Online Inverse Optimal Control for Time-Varying Cost Weights. Biomimetics 2024, 9, 84. Cao, S.; Luo, Z.; Quan, C. Online Inverse Optimal Control for Time-Varying Cost Weights. Biomimetics 2024, 9, 84.
Abstract
Inverse optimal control is a method for recovering the cost function used in an optimal control problem in expert demonstrations. Most studies on inverse optimal control have focused on building the unknown cost function through the linear combination of given features with unknown cost weights, which are generally considered to be constant. However, in many real-world applications, the cost weights may vary over time. In this study, we propose an adaptive online inverse optimal control approach based on a neural-network approximation to address the challenge of recovering time-varying cost weights. We conduct a well-posedness analysis of the problem and suggest a condition for the adaptive goal, under which the weights of the neural network generated to achieve this adaptive goal are unique to the corresponding inverse optimal control problem. Furthermore, we propose an updating law for the weights of the neural network to ensure the stability of the convergence of the solutions. Finally, simulation results for an example linear system are presented to demonstrate the effectiveness of the proposed strategy. The proposed method is applicable to a wide range of problems requiring real-time inverse optimal control calculations
Keywords
inverse optimal control; online calculation; time-varying cost weights; robust to noises
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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