Induction motor parameter estimation using disrupted black hole artificial bee colony algorithm. (2017)

• Record Type: Journal Article
• Authors: Sharma, Fani Bhushan; Kapoor, Shashi Raj
• Is Part Of: International journal of metaheuristics. Volume 6:Number 1/2(2017)
• Page Start: 85
• Page End: 106
• Publication Date: 2017
• Subjects: disrupted black hole -- disruption -- induction motors -- metaheuristics -- real-world optimisation -- swarm intelligence -- parameter estimation -- artificial bee colony -- ABC; Heuristic algorithms -- Periodicals; 006.3105
• Languages: English
• ISSNs: 1755-2176

Abstract

The most widespread motors in industries are induction motors nowadays. The design, performance evaluation and control of induction motors are based on circuit parameters. The accurate measurement of electrical parameters, like resistance (or reactance), is a tedious job. So, researchers have found induction motor parameter estimation as a significant optimisation aspect. Though conventional techniques produce good results, the swarm intelligence-motivated techniques produce still better results for real-world optimisation problems nowadays. In this paper, swarm intelligence-motivated artificial bee colony (ABC) algorithm is modified with physics's phenomena. The proposed algorithm is named as disrupted black hole ABC (DBHABC) algorithm. Further, this proposed algorithm is applied for optimising induction motor parameter estimation. The obtained outcomes reveal that DBHABC may be a good choice for induction motor parameter estimation.