Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive

M. A. Hannan, J. A. Ali, A. Mohamed, U. A.U. Amirulddm, Nadia Mei Lin Tan, M. N. Uddin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This study introduces a quantum-behaved lightening search algorithm (QLSA) to improve the search capability of every step leader to find a projectile position. The QLSA improves the indirect field-oriented fuzzy-PI controller technique to control a three-phase induction motor (TIM). The generated adaptive PI current control parameters and fuzzy membership functions (MFs) are carried to design induction motor (IM) drive speed controller to minimize the fitness function formulated by QLSA. An optimal QLSA-based indirect field-oriented control (QLSA-IFOC) fitness function is used to reduce the mean absolute error (MAE) of the rotor speed to improve the performance of the TIM with varying speed and mechanical load. Results obtained from the QLSA-IFOC are compared with those obtained through lightening search algorithm (LSA), gravitational search algorithm (GSA), backtracking search algorithm (BSA), and particle swarm optimization (PSO) to validate the developed controller. The optimization results of objective functions in terms of box plots and iterations show that the QLSA algorithm outperforms the other optimization algorithms. Moreover, the QLSA-IFOC controller performed well in all tests in terms of transient response. The developed controller also minimizes overshoot, increases damping capability and reduces of the root mean square error (RMSE) as well as standard division (SD) under sudden change of sped and mechanical loads.

Original languageEnglish
Title of host publication2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
Volume2017-January
ISBN (Electronic)9781509048946
DOIs
Publication statusPublished - 08 Nov 2017
Event2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 - Cincinnati, United States
Duration: 01 Oct 201705 Oct 2017

Other

Other2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
CountryUnited States
CityCincinnati
Period01/10/1705/10/17

Fingerprint

PI Control
Lightning
Fuzzy control
Fuzzy Control
Search Algorithm
Induction Motor
Controller
Controllers
Induction motors
Fitness Function
Box plot
Field Oriented Control
Minimise
Fuzzy Membership Function
PI Controller
Projectile
Overshoot
Backtracking
Transient Response
Control Function

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Hannan, M. A., Ali, J. A., Mohamed, A., Amirulddm, U. A. U., Tan, N. M. L., & Uddin, M. N. (2017). Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive. In 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 (Vol. 2017-January, pp. 1-8). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS.2017.8101736
Hannan, M. A. ; Ali, J. A. ; Mohamed, A. ; Amirulddm, U. A.U. ; Tan, Nadia Mei Lin ; Uddin, M. N. / Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive. 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-8
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abstract = "This study introduces a quantum-behaved lightening search algorithm (QLSA) to improve the search capability of every step leader to find a projectile position. The QLSA improves the indirect field-oriented fuzzy-PI controller technique to control a three-phase induction motor (TIM). The generated adaptive PI current control parameters and fuzzy membership functions (MFs) are carried to design induction motor (IM) drive speed controller to minimize the fitness function formulated by QLSA. An optimal QLSA-based indirect field-oriented control (QLSA-IFOC) fitness function is used to reduce the mean absolute error (MAE) of the rotor speed to improve the performance of the TIM with varying speed and mechanical load. Results obtained from the QLSA-IFOC are compared with those obtained through lightening search algorithm (LSA), gravitational search algorithm (GSA), backtracking search algorithm (BSA), and particle swarm optimization (PSO) to validate the developed controller. The optimization results of objective functions in terms of box plots and iterations show that the QLSA algorithm outperforms the other optimization algorithms. Moreover, the QLSA-IFOC controller performed well in all tests in terms of transient response. The developed controller also minimizes overshoot, increases damping capability and reduces of the root mean square error (RMSE) as well as standard division (SD) under sudden change of sped and mechanical loads.",
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Hannan, MA, Ali, JA, Mohamed, A, Amirulddm, UAU, Tan, NML & Uddin, MN 2017, Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive. in 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-8, 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017, Cincinnati, United States, 01/10/17. https://doi.org/10.1109/IAS.2017.8101736

Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive. / Hannan, M. A.; Ali, J. A.; Mohamed, A.; Amirulddm, U. A.U.; Tan, Nadia Mei Lin; Uddin, M. N.

2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-8.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This study introduces a quantum-behaved lightening search algorithm (QLSA) to improve the search capability of every step leader to find a projectile position. The QLSA improves the indirect field-oriented fuzzy-PI controller technique to control a three-phase induction motor (TIM). The generated adaptive PI current control parameters and fuzzy membership functions (MFs) are carried to design induction motor (IM) drive speed controller to minimize the fitness function formulated by QLSA. An optimal QLSA-based indirect field-oriented control (QLSA-IFOC) fitness function is used to reduce the mean absolute error (MAE) of the rotor speed to improve the performance of the TIM with varying speed and mechanical load. Results obtained from the QLSA-IFOC are compared with those obtained through lightening search algorithm (LSA), gravitational search algorithm (GSA), backtracking search algorithm (BSA), and particle swarm optimization (PSO) to validate the developed controller. The optimization results of objective functions in terms of box plots and iterations show that the QLSA algorithm outperforms the other optimization algorithms. Moreover, the QLSA-IFOC controller performed well in all tests in terms of transient response. The developed controller also minimizes overshoot, increases damping capability and reduces of the root mean square error (RMSE) as well as standard division (SD) under sudden change of sped and mechanical loads.

AB - This study introduces a quantum-behaved lightening search algorithm (QLSA) to improve the search capability of every step leader to find a projectile position. The QLSA improves the indirect field-oriented fuzzy-PI controller technique to control a three-phase induction motor (TIM). The generated adaptive PI current control parameters and fuzzy membership functions (MFs) are carried to design induction motor (IM) drive speed controller to minimize the fitness function formulated by QLSA. An optimal QLSA-based indirect field-oriented control (QLSA-IFOC) fitness function is used to reduce the mean absolute error (MAE) of the rotor speed to improve the performance of the TIM with varying speed and mechanical load. Results obtained from the QLSA-IFOC are compared with those obtained through lightening search algorithm (LSA), gravitational search algorithm (GSA), backtracking search algorithm (BSA), and particle swarm optimization (PSO) to validate the developed controller. The optimization results of objective functions in terms of box plots and iterations show that the QLSA algorithm outperforms the other optimization algorithms. Moreover, the QLSA-IFOC controller performed well in all tests in terms of transient response. The developed controller also minimizes overshoot, increases damping capability and reduces of the root mean square error (RMSE) as well as standard division (SD) under sudden change of sped and mechanical loads.

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BT - 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017

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Hannan MA, Ali JA, Mohamed A, Amirulddm UAU, Tan NML, Uddin MN. Quantum-behaved lightning search algorithm to improve indirect field-oriented fuzzy-PI control for im drive. In 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-8 https://doi.org/10.1109/IAS.2017.8101736