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Multi_Step_Dual_Control_for_Exploration_and_Exploitation_in_Autonomous_Search_with_Convergence_Guarantee__2_ (2).pdf (2.02 MB)

Multistep dual control for exploration and exploitation in autonomous search with convergence guarantee

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journal contribution
posted on 2024-03-27, 14:11 authored by Yuan Tan, Jun YangJun Yang, Wen-Hua ChenWen-Hua Chen, Shihua Li

Inspired by the concept of recently proposed dual control for exploration and exploitation, this paper presents a multi-step dual control for exploration and exploitation with guaranteed convergence in the search for autonomous sources. To deal with an unknown source position and environment, the proposed dual control algorithm faces significant challenges in demonstrating its recursive feasibility and convergence. With the help of the properties of Bayesian estimators, we redesign a multi-step dual control for exploitation and exploration algorithm with necessary terminal ingredients, and show that the recursive feasibility and the convergence of the modified dual control algorithm are guaranteed. Two simulation scenarios are conducted, which demonstrate that the proposed algorithm outperforms the stochastic model predictive control approach and the informative path planning approach in terms of searching successful rates and efficiency.

Funding

Goal-Oriented Control Systems (GOCS): Disturbance, Uncertainty and Constraints

Engineering and Physical Sciences Research Council

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National Natural Science Foundation of China under Grant 62025302 and Grant 61973081

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Industrial Informatics

Publisher

Institute of Electrical and Electronics Engineers

Version

  • AM (Accepted Manuscript)

Rights holder

Accepted manuscript © The Authors; publisher version © IEEE

Publisher statement

For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) license to any Accepted Manuscript version arising.

Acceptance date

2024-02-05

Publication date

2024-03-12

Copyright date

2024

ISSN

1551-3203

eISSN

1941-0050

Language

  • en

Depositor

Dr Jun Yang. Deposit date: 8 February 2024

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