Performance Evaluation of speed control using Fuzzy dependent Genetic Algorithm in PMSM. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Vijay Amirtha Raj, F.; Kamatchi Kannan, V.; Ponmurugan, P.; Chitra, K.; Lakshmanan, M.
• Is Part Of: IOP conference series. Volume 1084:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Artificial bee colony -- ANFIS -- Fuzzy Controller -- PID controller -- Genetic Algorithm -- PMSM -- Speed regulation; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1084/1/012087
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: This paper examines the role of the tuning algorithm for speed regulation of the Permanent Magnet Synchronous Motor (PMSM). The picks of the PID regulator normally provide adequate results in the application of a low-force drive, but for high-power application drives, a self PID controller doesn't provide any acceptable performance. Such applications require high-precision, superior and adaptable speed regulators and effectiveness in the cycle and execution of the plan. High-performance applications need some capacity based on High-speed high-reliability regulators, adaptability with maximum torque coefficient, higher rating capacity with minimum ripple torque. So many speed controlling mechanisms are available in the quick world, and these methods vary from the choice of regulator used in the PMSM to the method of programming/use of equipment. In this paper, generous examination is taken to control the speed of PMSM with three unique specialists, ABC based speed control drive, ANFIS controller of PMSM drive and Genetic algorithm based fuzzy controller. The planned regulators are tried through the mathematical reproductions in the MATLAB Simulink Platform. The examination between the reproduction aftereffects of execution measures are introduced toward the end. Hereditary calculation based Genetic algorithm based fuzzy controller gives some better outcome appropriate for the superior applications.