Document Type : Review Article

Authors

1 Young Researchers and elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

3 Department of Electrical and Computer Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

Abstract

In this article we investigate on robust mixed-sensitivity H∞ control for speed and torque control of induction motor (IM). In order to simplify the design procedure the Takagi–Sugeno (T–S) fuzzy approach is introduced to solve the nonlinear model Problem. Loop-shaping methodology and Mixed-sensitivity problem are developed to formulate frequency-domain specifications. Then  a regional  pole-placement output feedback H∞ controller is employed by using linear matrix inequalities(LMIs) teqnique for each linear subsystem of IM T-S fuzzy model. Parallel Distributed Compensation (PDC) is used to design the controller for the overall system . Simulation results are presented to validate the effectiveness of the proposed controller even in the presence of motor parameter variations and unknown load disturbance.  

Keywords

[1] M., Rodic, K., Jezernik, "Speed-sensorless sliding-mode torque control of an induction motor,". Industrial Electronics, IEEE Transactions , Vol.49, No. 1, pp.87–95, 2002 .
[2] J.C., Basilio et al, "Hinf design of rotor flux oriented current-controlled induction motor drives: speed control, noise attenuation and stability robustness ,". IET Control Theory, Vol. 4, No.11, pp. 2491 - 2505, Nov. 2010.
[3] R., Mario, P., Tomei and C.M., Verrelli, "A nonlinear tracking control for sensorless induction motors,". Automatica,Vol. 41, No. 6, pp. 1071-1077, June 2005.
[4] H.A., Yousef, M.A., Wahba, "Adaptive fuzzy mimo control of induction motors,". Expert Systems with Applications, Vol. 36, No. 3, pp. 4171-4175, Apr. 2009.
[5] [5]B.-S., Chen , C.-H., Wu, "Robust Optimal Reference-Tracking Design Method for Stochastic Synthetic Biology Systems”: T-S Fuzzy Approach. Fuzzy Systems, IEEE Transactions, Vol. 18, No. 6, pp. 1144-1159, Dec. 2010.
[6] R.-J., Wai , Z.W., Yang, "Adaptive Fuzzy Neural Network Control Design via a T-S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics,". Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions, Vol. 38, No. 5, pp. 1326-1346, Oct. 2008.
[7] V., Azimi, M.A., Nekoui and A., Fakharian. ," Robust multi-objective H2/ H∞ tracking control based on T-S fuzzy model for a class of nonlinear uncertain drive systems,". Proceeding of The Institution of Mech. Eng. Part I-Journal of Systems and Control Engineering, Vol.226, No. 8, pp. 1107–1118, 2012.
[8] V., Azimi, A., Fakharian and M.B., Menhaj " Position and current control of an Permanent-Magnet Synchronous Motor by using loop-shaping methodology: blending of H∞ mixed-sensitivity problem and T-S fuzzy model scheme,", Journal of Dynamic Systems Measurement and Control-Transactions of the ASME, Vol.135, No. 5, pp. 051006-1–051006-11, 2013.
[9] A., Fakharian, V., Azimi" Robust mixed-sensitivity H∞ control for a class of MIMO uncertain nonlinear IPM synchronous motor via TS fuzzy model " , Methods and Models in Automation and Robotics (MMAR), pp. 546-551, Poland, 2012.
[10] V., Azimi, A., Fakharian, M.B., Menhaj " Robust Mixed-Sensitivity Gain-Scheduled H∞ tracking control of a nonlinear Time-Varying IPMSM via a T-S fuzzy model", 9th France-Japan & 7th Europe-Asia Congress on and Research and Education in Mechatronics(REM), pp. 345-352, France, 2012.
[11] V., Azimi, M. B., Menhaj, A., Fakharian. "Robust H2/ H∞ Control for a Robot Manipulator Fuzzy System". 13th Iranian Conference on Fuzzy Systems (IFSC), Iran, 2013.
[12] V., Azimi, M. B., Menhaj, A., Fakharian. "Fuzzy Robust Control of MIMO Nonlinear Uncertain systems". 13th Iranian Conference on Fuzzy Systems (IFSC), Iran, 2013.
[13] M., Staroswiecki, G., Comtet-Varga, "Analytical redundancy relations for fult detection and isolation in algebric dynamic systems".Automatica, Vol. 37, No. 5, pp. 687-699, May 2001.
[14] W., Assawinchaichote, S.K.N., and P.S., "Fuzzy Control and Filter Design for Uncertain Fuzzy Systems,". Springer-Verlag Berlin Heidelberg, 2006.
[15] P., Gahinet, A.N., A. J., Laub and M., Chilali, "LMI Control Toolbox,". MathWorks, 1995.
[16] D.-W., Gu, P.H.P., and M.M.K., “Robust Control Design with MATLAB,". Springer-Verlag London, 2005..