Genetic Algorithms Based Fuzzy Speed C ontrollers for Indirect Field Oriented Control of Induction Motor Drive

In this paper the genetic algorithms is applied to automate and optimize the fuzzy controller design process. To do this, the normalization parameters, membership functions and decision table are converted into binary bit string. This optimization requires a predefined objective function. The task of such a design algorithm is the modification of the existing knowledge and at the same time, the investigation of new feasible structures. The proposed approach in this paper is employed for the speed control of an induction motor drive with indirect field oriented control.

[1]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[2]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[3]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[4]  Bhim Singh,et al.  Fuzzy logic based speed controller for vector controlled cage induction motor drive , 1998, Proceedings of IEEE TENCON '98. IEEE Region 10 International Conference on Global Connectivity in Energy, Computer, Communication and Control (Cat. No.98CH36229).

[5]  Hans-Jürgen Zimmermann,et al.  Introduction to Fuzzy Sets , 1985 .

[6]  Vitor Fernao Pires,et al.  A comparative study of a PI, neural network and fuzzy genetic approach controllers for an AC-drive , 1998, AMC'98 - Coimbra. 1998 5th International Workshop on Advanced Motion Control. Proceedings (Cat. No.98TH8354).

[7]  T. Nasser,et al.  Direct torque fuzzy controlled induction machine drive using an optimized extended Kalman filter , 2011, 2011 International Conference on Communications, Computing and Control Applications (CCCA).

[8]  M. Kamli,et al.  Design of a Fuzzy Sliding Mode Controller by Genetic Algorithms for Induction Machine Speed Control , 2004 .

[9]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[11]  M. R. Douiri,et al.  A neuro fuzzy PI controller used for speed control of a direct torque to twelve sectors controlled induction machine drive , 2011, 2011 International Conference on Multimedia Computing and Systems.

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  Toshihiko Noguchi,et al.  Field-oriented control of an induction motor with robust on-line tuning of its parameters , 1997 .

[14]  Masayoshi Tomizuka,et al.  Fuzzy gain scheduling of PID controllers , 1993, IEEE Trans. Syst. Man Cybern..