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Fast dual control of exploration and exploitation for autonomous search of hazardous sources

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conference contribution
posted on 2024-07-23, 16:04 authored by Toa Tran, Wen-Hua ChenWen-Hua Chen, Guoqiang Tan
This paper presents a new control algorithm designed for addressing the challenges posed by autonomous search problems, where the true source location and environment remain unknown. Utilizing a novel reward function, we formulate a fast dual control approach within the realm of optimization. This approach attains an optimal balance between exploration and exploitation by navigating the searcher towards the estimated source target while maximizing the exploration capability of control actions. The proposed algorithm not only demonstrates excellent search performance but also exhibits a high level of computational efficiency, as evidenced by two numerical examples provided for illustration.

Funding

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

Engineering and Physical Sciences Research Council

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

2024 IEEE International Conference on Industrial Technology (ICIT)

Source

2024 IEEE International Conference on Industrial Technology (ICIT)

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

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.

Publication date

2024-06-05

Copyright date

2024

ISBN

9798350340266; 9798350340273

ISSN

2641-0184

eISSN

2643-2978

Language

  • en

Location

Bristol, United Kingdom

Event dates

25th March 2024 - 27th March 2024

Depositor

Prof Wen-Hua Chen. Deposit date: 26 June 2024

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