{"references": ["C.M. Liaw, Y.S. Kung and C.M. Wu Design and implementation of a\nhigh-performance field-oriented induction motor drive. IEEE Trans. Ind.\nElectron.,vol.38,4,pp.275-282,1991.", "M.A. Wishart and R.G. Harley. Identification and control of induction\nmachines using artificial neural networks. IEEE Trans. Ind. Applicat.,\nvol.31,pp.612-619, 1995.", "Y.S. Kung, C.M. Liaw and M.S. Ouyang. Adaptive speed control for\ninduction motor drives using neural networks. IEEE Trans. Ind.\nElectron. Vol.42,1,pp.25-32, 1995.", "T.C. Chen and T.T. Sheu. Robust speed-controlled induction motor\ndrive based on model reference with neural networks. Inter. Journ. Of\nKnowledge Based Intelligent Engineering System. Vol.3,3.pp.162-171,\n1992.", "Levin and K.S. Narendra. Control dynamics systems using neural\nnetworks: Controllability and Stabilization . IEEE Trans. on Neural\nNetworks, Vol.4,No.2,March 1993.", "K.S. Narendra and K. Parthasarathy. Identification and control for\ndynamical systems using neural networks . IEEE Trans. Neural\nNetworks, NN-1,1,4-27, 1990.", "Y. Edward, Y. Ho and C. Paresh .Control dynamics of speed drive\nsystems using sliding mode controllers with integral compensation .\nIEEE Trans. On Industry Applications, Vol.,27, No.5, Sept-Oct. 1991.", "Jie Zhang and T.H. Burton. New approach to field orientation control of\nCSI induction motor drive. IEE Proceedings, Vol.135,Pt. B. No.1;\nJanuary 1988.", "B. Burton and F. Kamran. Identification and control of induction motor\nstator currents using fast on-line random training of neural networks .\nIEEE Trans. on Industry Applications, Vol.33,No.3,May-June,1997.\n[10] D. Nguyen and B. Widrow. Improving the learning speed of two layer\nneural networks by choosing initial values of adaptive weights. Proc. Int.\nJoint Conf. Neural Networks, San Diego, CA, pp.21-26, july, 1990.\n[11] G.C.D. Souza, B.K. Bose and J.G. Cleland. Fuzzy logic based on-line\nefficiency optimization control of an indirect vector controlled induction\nmotor drive, IEEE-IECOM Conf. Maui, HI, pp.1168-1174, november\n1993.\n[12] G.C.D. Souza and B.K. Bose. A fuzzy set theory based control of a\nphase controlled converter DC machine drive, IEE-IAS Annu. Meeting\nConf. Rec., Dearborn, MI, pp.854-861, October 1991.\n[13] Q. Li , S.K. Tso and A.N. Poo. PID tuning using neural networks,\nIntelligent Automation and Control TSI Press Inc., USA, pp.461-465,\n1998."]}

In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.