Induction Motor Control Using Two Intelligent Algorithms Analysis

The main drawbacks of classical direct torque control (C-DTC) are: the high torque and flux ripples and variable switching frequency. To overcome these problems, two intelligent control theories, namely fuzzy logic control (FLC) and neuro-fuzzy control (NFC) are introduced to replace the hysteresis comparators and lookup table of the C-DTC for induction motor drive. The effectiveness and feasibility of the proposed approaches have been demonstrated through computer simulations. A comparison study between the C-DTC, FL-DTC and NF-DTC has been made in order to confirm the validity of the proposed schemes. The superiority of the NF-DTC has been proved through comparative simulation results.

[1]  Seiji Kondo,et al.  Enlarging switching frequency in direct torque-controlled inverter by means of dithering , 1999 .

[2]  Vilém Novák,et al.  Reasoning about mathematical fuzzy logic and its future , 2012, Fuzzy Sets Syst..

[3]  Toshihiko Noguchi,et al.  A New Quick-Response and High-Efficiency Control Strategy of an Induction Motor , 1986, IEEE Transactions on Industry Applications.

[4]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.

[5]  A. Tani,et al.  FOC and DTC: two viable schemes for induction motors torque control , 2002 .

[6]  Xin Wei,et al.  Minimization of torque ripple of direct-torque controlled induction machines by improved discrete space vector modulation , 2004 .

[7]  Chin-Teng Lin,et al.  Neural-Network-Based Fuzzy Logic Control and Decision System , 1991, IEEE Trans. Computers.

[8]  M. Depenbrock,et al.  Direct self-control (DSC) of inverter-fed induction machine , 1988 .

[9]  Sadegh Vaez-Zadeh,et al.  Combined vector control and direct torque control method for high performance induction motor drives , 2007 .

[10]  Yen-Shin Lai,et al.  A New Approach to Direct Torque Control of Induction Motor Drives for Constant Inverter Switching Frequency and Torque Ripple Reduction Yen-Shin Lai, Member, IEEEand Jian-Ho Chen , 2001 .

[11]  Hoang Le-Huy.  Comparison of field-oriented control and direct torque control for induction motor drives , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).

[12]  Ming-Ji Yang,et al.  Global Minimum Torque Ripple Design for Direct Torque Control of Induction Motor Drives , 2010, IEEE Transactions on Industrial Electronics.

[13]  Chun-Fei Hsu,et al.  Adaptive asymmetric fuzzy neural network controller design via network structuring adaptation , 2008, Fuzzy Sets Syst..

[14]  Robert Babuska,et al.  Fuzzy Logic Control: Advances in Applications , 1999 .

[15]  Peter B. Andrews.  An introduction to mathematical logic and type theory - to truth through proof , 1986, Computer science and applied mathematics.

[16]  Detlef Nauck,et al.  Foundations Of Neuro-Fuzzy Systems , 1997 .

[17]  Hideyuki Takagi,et al.  Neural networks designed on approximate reasoning architecture and their applications , 1992, IEEE Trans. Neural Networks.