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Volume 13
Issue 23
10.3390/electronics13234655
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making

by
Qinghai Zhang
,
Xiaoqian Zhang
*,
Qingjian Zhao
,
Shuang Zhao
,
Yanan Zhao
,
Yang Guo
and
Zhengxu Zhao
Institute of Complex Networks and Visualisations, Qingdao University of Technology, Qingdao 266520, China
*
Author to whom correspondence should be addressed.
Electronics 2024, 13(23), 4655; https://doi.org/10.3390/electronics13234655
Submission received: 15 October 2024 / Revised: 16 November 2024 / Accepted: 21 November 2024 / Published: 25 November 2024
Versions Notes

Abstract

The design of an Active Reflective Surface Control System (ARCS) is a complex engineering task involving multidimensional and multi-criteria constraints. This paper proposes a novel methodological approach for ARCS design and optimization by integrating Axiomatic Design (AD) and Multi-Criteria Decision Making (MCDM) techniques. Initially, a structured design plan is formulated within the axiomatic design framework. Subsequently, four MCDM methods—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Entropy Weight Method (EWM), Multi-Criteria Optimization and Compromise Solution (VIKOR), and the integrated TOPSIS–Grey Relational Analysis (GRA) approach—are used to evaluate and compare the alternative solutions. Additionally, fuzzy information axioms are used to calculate the total information content for each alternative to identify the optimal design. A case study is conducted, selecting the optimal actuator for a 5 m diameter scaled model of the Five-hundred-meter Aperture Spherical radio Telescope (FAST), followed by digital control experiments on the chosen actuator. Based on the optimal design scheme, an ARCS prototype is constructed, which accelerates project completion and substantially reduces trial-and-error costs.
Keywords: active reflector control system; axiomatic design; multi-criteria decision making; design scheme; control experiment active reflector control system; axiomatic design; multi-criteria decision making; design scheme; control experiment

Share and Cite

MDPI and ACS Style

Zhang, Q.; Zhang, X.; Zhao, Q.; Zhao, S.; Zhao, Y.; Guo, Y.; Zhao, Z. An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making. Electronics 2024, 13, 4655. https://doi.org/10.3390/electronics13234655

AMA Style

Zhang Q, Zhang X, Zhao Q, Zhao S, Zhao Y, Guo Y, Zhao Z. An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making. Electronics. 2024; 13(23):4655. https://doi.org/10.3390/electronics13234655

Chicago/Turabian Style

Zhang, Qinghai, Xiaoqian Zhang, Qingjian Zhao, Shuang Zhao, Yanan Zhao, Yang Guo, and Zhengxu Zhao. 2024. "An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making" Electronics 13, no. 23: 4655. https://doi.org/10.3390/electronics13234655

APA Style

Zhang, Q., Zhang, X., Zhao, Q., Zhao, S., Zhao, Y., Guo, Y., & Zhao, Z. (2024). An Optimization Method for Design Solutions to Active Reflective Surface Control Systems Based on Axiomatic Design and Multi-Criteria Decision Making. Electronics, 13(23), 4655. https://doi.org/10.3390/electronics13234655

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