Speed and Torque Control of Induction Motor Using Adaptive Neuro-Fuzzy Interference System with DTC

被引:1
|
作者
Bindal, Ranjit Kumar [1 ]
Kaur, Inderpreet [1 ]
机构
[1] Chandigarh Univ, Elect Engn Dept, Mohali, Punjab, India
关键词
Three-phase induction motor; Adaptive Neuro-Fuzzy Interference System (ANFIS) direct torque control; FEEDBACK-LINEARIZATION; FLUX CONTROL; IMPLEMENTATION; DRIVE; NETWORK;
D O I
10.1007/978-981-13-3140-4_73
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Every industry needs speed and torque ripple control of induction motor in large number of applications. The number of induction motor takes more time during starting, settling and transient period. As more time is taken by the motor so there are more losses, more heat, less efficiency and more ripples are produced. To overcome these drawback, direct torque control technique known as conventional technique, is used with induction motors, but with up to certain limits the drawbacks are reduced. In this paper a new technique an Adaptive Neuro-Fuzzy Interference System (ANFIS) with DTC is proposed to overcome the drawbacks of conventional DTC technique. Now by implementing and comparing the proposed technique ANFIS with conventional one it is seen that the system becomes less complicated, the performance of the speed and torque control of the induction motor is also improved. It is also seen that as we compared the proposed technique with conventional one the rise time is reduced by 256 ms settling time is reduced by 687 ms and transient time is reduced by 202 ms and torque ripples are also reduced and the overall performance of the induction motor is improved.
引用
收藏
页码:815 / 825
页数:11
相关论文
共 50 条
  • [1] Adaptive neuro-fuzzy control of an induction motor
    Areed, Fayez G.
    Haikal, Amira Y.
    Mohammed, Reham H.
    AIN SHAMS ENGINEERING JOURNAL, 2010, 1 (01) : 71 - 78
  • [2] An adaptive speed controller for induction motor drives using adaptive neuro-fuzzy inference system
    Chao, Kuei-Hsiang
    Shen, Yu-Ren
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF THEORETICAL AND METHODOLOGICAL ISSUES, 2007, 4681 : 381 - +
  • [3] Adaptive neuro-fuzzy control of the sensorless induction motor drive system
    Orlowska-Kowalska, Teresa
    Dybkowski, Mateusz
    Szabat, Krzysztof
    2006 12TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE, VOLS 1-4, 2006, : 685 - +
  • [4] Direct-Torque Neuro-Fuzzy Control of Induction Motor
    XU JunpengCHEN YanfengLI GuohouDepartment of Electronic EngineeringHenan Institute of Science TechnologyXinxiang China
    河南科技学院学报(自然科学版), 2007, (03) : 62 - 65
  • [5] Direct Torque neuro-fuzzy Control of induction motor drive
    Grabowski, PZ
    IECON '97 - PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS, CONTROL, AND INSTRUMENTATION, VOLS. 1-4, 1997, : 557 - 562
  • [6] NEURO-GENETIC OBSERVER SPEED FOR DIRECT TORQUE NEURO-FUZZY CONTROL OF INDUCTION MOTOR DRIVE
    Douiri, Moulay Rachid
    Cherkaoui, Mohamed
    Essadki, Ahmed
    JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2012, 21 (07)
  • [7] Direct Torque Control of Induction Motor Drive System with Adaptive Sliding-Mode Neuro-Fuzzy Compensator
    Dybkowski, Mateusz
    Szabat, Krzysztof
    2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2015, : 714 - 719
  • [8] Speed Control of Switched Reluctance Motor Using an Adaptive Neuro-fuzzy Controller
    Hasanien, Hany M.
    WORLD CONGRESS ON ENGINEERING - WCE 2013, VOL II, 2013, : 1093 - 1096
  • [9] An Adaptive Neuro-Fuzzy Based Speed Sensorless Induction Motor Drives
    Gupta, R. A.
    Kumar, Rajesh
    Surjuse, Rajesh S.
    2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 396 - 401
  • [10] Adaptive Neuro-fuzzy Inference system into Induction Motor : Estimation
    Boussada, Zina
    Ben Hamed, Mouna
    Sbita, Lassaad
    2014 INTERNATIONAL CONFERENCE ON ELECTRICAL SCIENCES AND TECHNOLOGIES IN MAGHREB (CISTEM), 2014,