Optimized speed controller for induction motor drive using quantum lightning search algorithm

Jamal Abd Ali, M. A. Hannan, Azah Mohamed

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

© 2016 IEEE. This paper presents an improve proportional-integral-derivative (PID) controller design technique for controlling a three-phase induction motor (TIM) speed drive using quantum lightning search algorithm (QLSA). This proposed controller avoids the exhaustive conventional trial- and-error procedure for obtaining PID parameters. Objective function using in the proposed controller is mean absolute error (MAE) to enhance the TIM speed performance under sudden change of the speed and load conditions. The QLSA is used to improve two controller system PID and PI controllers in the TIM drive. Moreover, the QLSA algorithm comperes with three optimization algorithms, namely, lightning search algorithm (LSA), the backtracking search algorithm (BSA), the particle swarm optimization (PSO). Designed and validated the simulation model by using a MATLAB/Simulink environment. Results show that the QLSA-based PID and PI speed controller is achieved better results than the other optimization controllers through reduce of damping capability, enhance the transient response, minimize the MAE, root mean square error (RMSE) and standard division (SD) of the speed response.
Original languageEnglish
Pages511-516
Number of pages459
DOIs
Publication statusPublished - 16 Jun 2017
EventPECON 2016 - 2016 IEEE 6th International Conference on Power and Energy, Conference Proceeding -
Duration: 16 Jun 2017 → …

Conference

ConferencePECON 2016 - 2016 IEEE 6th International Conference on Power and Energy, Conference Proceeding
Period16/06/17 → …

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All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Energy(all)
  • Mechanical Engineering
  • Management, Monitoring, Policy and Law

Cite this

Ali, J. A., Hannan, M. A., & Mohamed, A. (2017). Optimized speed controller for induction motor drive using quantum lightning search algorithm. 511-516. Paper presented at PECON 2016 - 2016 IEEE 6th International Conference on Power and Energy, Conference Proceeding, . https://doi.org/10.1109/PECON.2016.7951615