Adaptive control of DC motor using bacterial foraging algorithm

被引:51
|
作者
Bhushan, Bharat [1 ]
Singh, Madhusudan [1 ]
机构
[1] Delhi Technol Univ, Dept Elect Engn, Delhi, India
关键词
Bacterial foraging algorithm; Identification; Adaptive control; Genetic algorithm; DC motor; IDENTIFICATION; DESIGN;
D O I
10.1016/j.asoc.2011.06.008
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces a bacterial foraging algorithm (BFA) based high performance speed control system for a DC motor. The rotor speed of the DC motor is being made to follow an arbitrary selected trajectory. The unknown nonlinear dynamics of the motor and the load are captured by BFA. The trained BFA identifier is used with a desired reference model to achieve trajectory control of DC motor. In this paper bacterial foraging algorithm (BFA) has been implemented for identification and control of DC motor. Simulation study on proposed system has been carried out in MATLAB. System nonlinearities alpha and beta have been estimated using BFA and compared with actual plant nonlinearities of dynamical system. In tracking of motor speed using BFA based controller the performance of the motor have been observed and compared with reference one. Performance study of DC motor has been carried out through genetic algorithm (GA) also. A comparison of performance analysis using BFA controller and that of GA for trajectory tracking shows that BFA based adaptive controller works effectively for tracking the desired trajectory in DC motor with less computational time. (C) 2011 Elsevier B. V. All rights reserved.
引用
收藏
页码:4913 / 4920
页数:8
相关论文
共 50 条
  • [31] An accurate and economical approach for induction motor field efficiency estimation using bacterial foraging algorithm
    Sakthivel, V. P.
    Bhuvaneswari, R.
    Subramanian, S.
    MEASUREMENT, 2011, 44 (04) : 674 - 684
  • [32] Robust Adaptive Sliding Mode Control Design with Genetic Algorithm for Brushless DC Motor
    Putra, Een Hutama
    Has, Zulfatman
    Effendy, Machmud
    2018 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTER SCIENCE AND INFORMATICS (EECSI 2018), 2018, : 330 - 335
  • [33] Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor
    Alejandro-Sanjines, Ulbio
    Maisincho-Jivaja, Anthony
    Asanza, Victor
    Lorente-Leyva, Leandro L.
    Peluffo-Ordonez, Diego H.
    BIOMIMETICS, 2023, 8 (05)
  • [34] Control of DC Motor Using Genetic Algorithm Based PID Controller
    Tiwari, Shubham
    Bhatt, Ankit
    Unni, Arjun C.
    Singh, Jai Govind
    Ongsakul, Weerakorn
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE AND UTILITY EXHIBITION ON GREEN ENERGY FOR SUSTAINABLE DEVELOPMENT (ICUE 2018), 2018,
  • [35] Adaptive Minimum Variance Control of a DC motor
    Zidane, Z.
    Lafkih, M. Ait
    Ramzi, M.
    Abounada, A.
    18TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, 2010, : 1 - 4
  • [36] Neural adaptive tracking control of a DC motor
    Horng, JH
    INFORMATION SCIENCES, 1999, 118 (1-4) : 1 - 13
  • [37] Discrete-time algorithm for generalized simplified adaptive control and its application to DC motor control
    Shibata, H
    Sun, Y
    Fujinaka, T
    Maruoka, G
    PROCEEDINGS OF THE 1996 IEEE IECON - 22ND INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS, CONTROL, AND INSTRUMENTATION, VOLS 1-3, 1996, : 332 - 339
  • [38] Robust Control of DC motor Using Fuzzy Sliding Mode Control and Genetic Algorithm
    Moghaddas, Mahbubeh
    Dastranj, Mohamad Reza
    Changizi, Nemat
    Rouhani, Modjtaba
    JOURNAL OF MATHEMATICS AND COMPUTER SCIENCE-JMCS, 2011, 2 (04): : 572 - 579
  • [39] Speed control of DC-DC converter fed DC motor using robust adaptive intelligent controller
    Prakash, Raghupathy
    Vasanthi, R.
    JOURNAL OF VIBRATION AND CONTROL, 2015, 21 (15) : 3107 - 3120
  • [40] PID Algorithm used for DC Motor Control
    Taut, M. A.
    Chindris, G.
    Pitica, D.
    2018 IEEE 24TH INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME), 2018, : 365 - 372