An Artificial Bee Optimization Based on Command Filtered CDM-Backstepping for Electro-Pneumatic System

  • Fouad Haouari ORCID
    Affiliation

    Department of Industrial Engineering and Maintenance, Ecole Nationale Supérieure de Technologie (ENST), Cité Diplomatique, Ex Centre Biomédical, Dergana, Bordj El Kiffan, 16078 Algiers, Algeria

  • Rabah Gouri
    Affiliation

    Department of Industrial Engineering and Maintenance, Ecole Nationale Supérieure de Technologie (ENST), Cité Diplomatique, Ex Centre Biomédical, Dergana, Bordj El Kiffan, 16078 Algiers, Algeria

  • Nourdine Bali
    Affiliation

    Department of Electrical Engineering, Faculty of Electronics and Computer Science, University of Sciences and Technology Houari Boumediene (USTHB), 16111 Algiers, Bab Ezzouar, P. O. B. 32, Algeria

  • Mohamed Tadjine
    Affiliation

    Process Control Laboratory, Department of Electrical Engineering, Ecole Nationale Polytechnique (ENP), 10 Avenue Hassan Badi, El Harrach, 16200 Algiers, Algeria

  • Mohamed Seghir Boucherit
    Affiliation

    Process Control Laboratory, Department of Electrical Engineering, Ecole Nationale Polytechnique (ENP), 10 Avenue Hassan Badi, El Harrach, 16200 Algiers, Algeria

Abstract

The proposed manuscript presents a coefficient diagram method (CDM) controller for an electro-pneumatic system. In order to tune the controller parameters, an artificial bee colony (ABC) optimization method is applied. According to the simulation results, the optimized parameters can provide better dynamic and steady state performances and higher robustness to the control algorithm, than the conventional tuned parameters.

Keywords: artificial bee optimization, command filtered backstepping, coefficients diagram method, pneumatic actuator
Published online
2019-08-15
How to Cite
Haouari, F., Gouri, R., Bali, N., Tadjine, M., Boucherit, M. S. “An Artificial Bee Optimization Based on Command Filtered CDM-Backstepping for Electro-Pneumatic System”, Periodica Polytechnica Electrical Engineering and Computer Science, 63(3), pp. 235-241, 2019. https://doi.org/10.3311/PPee.14077
Section
Articles