Article: Computer intelligent device adjustment and fuzzy controller design for embedded ARM Journal: International Journal of Embedded Systems (IJES) 2023 Vol.16 No.5/6 pp.385 - 392 Abstract: There are more and more researches on fuzzy control. Fuzzy controllers in all walks of life have very successful application cases, but they can be affected by quantification factors in the development process, so most of the control rules obtained are based on personal experience and have great uncertainty. To solve these problems, in this paper, the intelligent device fuzzy controller was designed and studied with the help of advanced reduced instruction set computing (RISC). The optimal control rules were searched by advanced RISC machines (ARM). These rules were used to generate the corresponding fuzzy controller. The experimental results suggested that the fuzzy controller based on embedded ARM was more accurate for the regulation of computer intelligence devices than the controllers based on ant algorithm and genetic algorithm. The accuracy of the controller studied in this paper was above 94%, while the other two adjustments were below 91% and 92%, respectively. The performance of the controller studied in this paper is also better, which is conducive to improve the performance of computer intelligent equipment, improve the use value of equipment, better improve the accuracy of equipment adjustment, improve the processing speed of fuzzy controller for subset rules, and the running speed is faster. Inderscience Publishers - linking academia, business and industry through research

Title: Computer intelligent device adjustment and fuzzy controller design for embedded ARM

Authors: Hansong Ge; Ke Li

Addresses: School of Information Technology, Shangqiu Normal University, Shangqiu 476000, Henan, China ' School of Information Technology, Shangqiu Normal University, Shangqiu 476000, Henan, China

Abstract: There are more and more researches on fuzzy control. Fuzzy controllers in all walks of life have very successful application cases, but they can be affected by quantification factors in the development process, so most of the control rules obtained are based on personal experience and have great uncertainty. To solve these problems, in this paper, the intelligent device fuzzy controller was designed and studied with the help of advanced reduced instruction set computing (RISC). The optimal control rules were searched by advanced RISC machines (ARM). These rules were used to generate the corresponding fuzzy controller. The experimental results suggested that the fuzzy controller based on embedded ARM was more accurate for the regulation of computer intelligence devices than the controllers based on ant algorithm and genetic algorithm. The accuracy of the controller studied in this paper was above 94%, while the other two adjustments were below 91% and 92%, respectively. The performance of the controller studied in this paper is also better, which is conducive to improve the performance of computer intelligent equipment, improve the use value of equipment, better improve the accuracy of equipment adjustment, improve the processing speed of fuzzy controller for subset rules, and the running speed is faster.

Keywords: fuzzy controller design; intelligent device adjustment; embedded ARM; ant algorithm; genetic algorithm.

DOI: 10.1504/IJES.2023.141939

International Journal of Embedded Systems, 2023 Vol.16 No.5/6, pp.385 - 392

Received: 11 Apr 2023
Accepted: 16 Sep 2023
Published online: 03 Oct 2024 *

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Title: Computer intelligent device adjustment and fuzzy controller design for embedded ARM

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