Performance Comparison of Dynamic Responses & Speed Control of Switched Reluctance Motor Using PI & Fuzzy logic Controller

被引：0
作者：
Jegadeeswari, G. [1 ]
Ezhilarasi, G. [2 ]
Pramila, V. [3 ]
Vijayanand, J. [4 ]
Kirubadurai, B. [5 ]
机构：
[1] AMET Deemed Be Univ, Dept EEE, Chennai, Tamil Nadu, India
[2] Sri Sairam Inst Technol, Dept EEE, Chennai, Tamil Nadu, India
[3] Abdur Rahman Inst Sci & Tech, Dept EEE, Chennai, Tamil Nadu, India
[4] JNN Inst Engn, Dept EEE, Chennai, Tamil Nadu, India
[5] VelTech Dr Rangarajan Dr Sagunthala R&D Inst Sci, Dept Aeronaut Engn, Chennai, Tamil Nadu, India
来源：
2023 9TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS, ICEES | 2023年
关键词：
Switched Reluctance Motor; PI Controller; Fuzzy logic; ship propulsion; Hysteresis current controller; speed regulation and Torque ripple; PARTICLE SWARM OPTIMIZATION;
D O I：
10.1109/ICEES57979.2023.10110237
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The notion of employing the Switched Reluctance Motor (SRM) as a replacement to Ship Electric propulsion Technology is presented in this paper. The speed control of a switched reluctance motor (SRM) is created by several adaptive controllers to demonstrate the effectiveness of the SRM. The reliability of the switching reluctance motor is tested in this study by submitting it to five major criteria such as speed settling time, peak overshoot, rise time, and peak time. For the regulated purpose of the switched reluctance motor, two various controllers, namely standard PI controllers and fuzzy, logic controller are utilised, and their behaviours are compared and analysed. The work is entirely done in the MATLAB/SIMULINK platform. Based on the efficacy of the controllers, the results were analysed and summarised. The simulation findings reveal that the SRM-based drive system with fuzzy logic controller has increased transient and steady-state efficiency and stability.
引用
收藏
页码：674 / 680
页数：7
相关论文
共 15 条
  • [1] Comparison of PM motor structures and sensorless control techniques for zero-speed rotor position detection
    Bianchi, Nicola
    Bolognani, Slilverio
    Jang, Ji-Hoon
    Sul, Seung-Ki
    [J]. IEEE TRANSACTIONS ON POWER ELECTRONICS, 2007, 22 (06) : 2466 - 2475
  • [2] Dutta P, 2014, INT C CONTR, DOI [10.1109/CIEC.2014.6959130, DOI 10.1109/CIEC.2014.6959130]
  • [3] Fogel DB, 2006, PRESS SERIES COMPUTA, V3rd, P128
  • [4] A particle swarm optimization approach for optimum design of PID controller in AVR system
    Gaing, ZL
    [J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 2004, 19 (02) : 384 - 391
  • [5] Automatic Operation of Accommodation Ladder on Tidal Ports
    Jegadeeswari, G.
    Kirubadurai, B.
    Dhanasekar, P.
    Viknesh, S.
    [J]. 2021 IEEE CONFERENCE ON NORBERT WIENER IN THE 21ST CENTURY (21CW): BEING HUMAN IN A GLOBAL VILLAGE, 2021,
  • [6] Jegadeeswari G., 2020, INT J SCI TECHNOLOGY, V9, P5425
  • [7] Jegadeeswari G., 2017, J ADV RES DYNAMICAL, V11, P638
  • [8] Kennedy, 2001, SWARM INTELL-US, DOI [10.1016/B978-1-55860-595-4.X5000-1, DOI 10.1016/B978-1-55860-595-4.X5000-1]
  • [9] Kennedy J., 2006, HDB NATURE INSPIRED, P187, DOI [10.1007/0-387-27705-6_6, DOI 10.1007/0-387-27705-6_6]
  • [10] Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design
    Panda, Sidhartha
    Padhy, Narayana Prasad
    [J]. APPLIED SOFT COMPUTING, 2008, 8 (04) : 1418 - 1427
12