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Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model

Wenyan Gong, Dechao Chen, Shuai Li Orcid Logo

IEEE Access, Volume: 8, Pages: 25976 - 25989

Swansea University Author: Shuai Li Orcid Logo

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Abstract

Conventional biological-heuristic solutions via zeroing neural network (ZNN) models have achieved preliminary efficiency on time-dependent nonlinear optimization problems handling. However, the investigation on finding a feasible ZNN model to solve the time-dependent nonlinear optimization problems...

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Published in: IEEE Access
ISSN: 2169-3536
Published: Institute of Electrical and Electronics Engineers (IEEE) 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa53713
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spelling 2020-10-23T13:59:21.3041263 v2 53713 2020-03-03 Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model 42ff9eed09bcd109fbbe484a0f99a8a8 0000-0001-8316-5289 Shuai Li Shuai Li true false 2020-03-03 MECH Conventional biological-heuristic solutions via zeroing neural network (ZNN) models have achieved preliminary efficiency on time-dependent nonlinear optimization problems handling. However, the investigation on finding a feasible ZNN model to solve the time-dependent nonlinear optimization problems with both inequality and equality constraints still remains stagnant because of the nonlinearity and complexity. To make new progresses on the ZNN for time-dependent nonlinear optimization problems solving, this paper proposes a biological-heuristic optimization model, i.e., inequality and equality constrained optimization ZNN (IECO-ZNN). Such a proposed IECO-ZNN breaks the conditionality that the solutions via ZNN for solving nonlinear optimization problems can not consider the inequality and equality constraints at the same time. The time-dependent nonlinear optimization problem subject to inequality and equality constraints is skillfully converted to a time-dependent equality system by exploiting the Lagrange multiplier rule. The design process for the IECO-ZNN model is presented together with its new architecture illustrated in details. In addition, the conversion equivalence, global stability as well as exponential convergence property are theoretically proven. Moreover, numerical studies, real-world applications to robot arm active sensing, and comparisons sufficiently verify the effectiveness and superiority of the proposed IECO-ZNN model for the time-dependent nonlinear optimization with inequality and equality constraints. Journal Article IEEE Access 8 25976 25989 Institute of Electrical and Electronics Engineers (IEEE) 2169-3536 Zeroing neural networks (ZNNs); biological-heuristic optimization; nonlinear optimization; inequality and equality constraints; robot motion control 3 2 2020 2020-02-03 10.1109/access.2020.2971020 COLLEGE NANME Mechanical Engineering COLLEGE CODE MECH Swansea University 2020-10-23T13:59:21.3041263 2020-03-03T10:58:46.6274274 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Wenyan Gong 1 Dechao Chen 2 Shuai Li 0000-0001-8316-5289 3 53713__16748__4f44f2c3d13a4c14ab3322e85eca4e13.pdf gong2020.pdf 2020-03-03T11:08:03.9192166 Output 5342515 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution 4.0 License (CC-BY). true eng http://creativecommons.org/licenses/by/4.0/
title Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
spellingShingle Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
Shuai Li
title_short Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
title_full Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
title_fullStr Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
title_full_unstemmed Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
title_sort Active Sensing of Robot Arms Based on Zeroing Neural Networks: A Biological-Heuristic Optimization Model
author_id_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8
author_id_fullname_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8_***_Shuai Li
author Shuai Li
author2 Wenyan Gong
Dechao Chen
Shuai Li
format Journal article
container_title IEEE Access
container_volume 8
container_start_page 25976
publishDate 2020
institution Swansea University
issn 2169-3536
doi_str_mv 10.1109/access.2020.2971020
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
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description Conventional biological-heuristic solutions via zeroing neural network (ZNN) models have achieved preliminary efficiency on time-dependent nonlinear optimization problems handling. However, the investigation on finding a feasible ZNN model to solve the time-dependent nonlinear optimization problems with both inequality and equality constraints still remains stagnant because of the nonlinearity and complexity. To make new progresses on the ZNN for time-dependent nonlinear optimization problems solving, this paper proposes a biological-heuristic optimization model, i.e., inequality and equality constrained optimization ZNN (IECO-ZNN). Such a proposed IECO-ZNN breaks the conditionality that the solutions via ZNN for solving nonlinear optimization problems can not consider the inequality and equality constraints at the same time. The time-dependent nonlinear optimization problem subject to inequality and equality constraints is skillfully converted to a time-dependent equality system by exploiting the Lagrange multiplier rule. The design process for the IECO-ZNN model is presented together with its new architecture illustrated in details. In addition, the conversion equivalence, global stability as well as exponential convergence property are theoretically proven. Moreover, numerical studies, real-world applications to robot arm active sensing, and comparisons sufficiently verify the effectiveness and superiority of the proposed IECO-ZNN model for the time-dependent nonlinear optimization with inequality and equality constraints.
published_date 2020-02-03T04:03:13Z
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