Optimal GainsTuning of Speed Controller in Induction Motor Drives Using Particle SWARMOptimization | ||||
| ERJ. Engineering Research Journal | ||||
| Article 6, Volume 37, Issue 1, January 2014, Page 1-12 PDF (1.33 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2014.66867 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Hussein M Wally1; Haitham Z. Azazi2; Fahmy M. El-Khouly3 | ||||
| 1Mechanical& Electrical Research Center, National Water Research Center, Egypt | ||||
| 2Department of electrical Engineering, Faculty of Engineering, Menoufiya University, Egypt | ||||
| 3Department of electrical Engineering, Faculty of Engineering, Menoufiya University, Egypt, | ||||
| Abstract | ||||
| The last decade has witnessed a great interest in using evolutionary algorithms (EAs), such as genetic algorithms (GA), evolutionary strategies and particle swarm optimization (PSO), for multivariate optimization. This paper presents a modern approach of speed control for three-phase induction motor (IM) using PSO algorithm to optimize the parameters of the proportional integral (PI) and Fuzzy-PI controllers. Comparison between different controllers is achieved, using PI and fuzzy-PI controllers which are tuned by two methods, firstly manually and secondly using PSO technique. Hybrid of FL and PI controller PSO-based for the speed control of given motor is also performed to eliminate the drawbacks of PI controller (overshoot, undershoot) and FL controller (steady-state error), which has a minimum number of fuzzy rules and membership functions (MFs). The overall system is simulated under various operating conditions and experimental results are prepared. | ||||
| Keywords | ||||
| Evolutionary Algorithms (EAs); Genetic Algorithms (GA); particle swarm optimization (PSO); Fuzzy Logic (FL); Membership Functions (MFs) | ||||
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