IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 10, NO. 3, JUNE 2002 375 Brief Papers_______________________________________________________________________________ Speed Control of Induction Motors Using a Novel Fuzzy Sliding-Mode Structure F. Barrero, A. González, A. Torralba, E. Galván, and L. G. Franquelo Abstract—This paper presents a new approach to indirect vector control of induction motors. Two nonlinear controllers, one of sliding mode type and the other PI-fuzzy logic-based, define a new control structure. Both controllers are combined by means of an expert system based on Takagi–Sugeno fuzzy reasoning. The sliding-mode controller acts mainly in a transient state while the PI-like fuzzy controller acts in the steady state. The new structure embodies the advantages that both nonlinear controllers offer: sliding-mode controllers increasing system stability limits and PI-like fuzzy logic based controllers reducing the chattering in permanent state. The scheme has been implemented and experimentally validated. Index Terms—Fuzzy logic-based control, hybrid control, sliding- mode control, speed induction motor drives, stability analysis. NOMENCLATURE . . Weighting factor. Friction constant. Output of the SLMC. Output of the FLBC. Global control action before the integrator. Flux component of the stator current. Torque component of the stator current. Inertial constant. Proportional torque constant. Number of rules. Load torque. Rotor time constant. Control action integration constant. Measured speed. Desired speed. Slip speed. Values of the membership functions corresponding to each rule and evaluated with the input values. Global control action before the integrator by defi- nition is equal to . Value of the output of the fuzzy controller evaluated with the input values. Values of the output Singletons that is inferred by the rule . Manuscript received February 12, 2001; revised August 10, 2001 and November 5, 2001. This work was supported in part by the Spanish Comisión Internacional de Ciencia y Tecnología under Project TAP-95-0371. The authors are with the Departimento de Ingeniería Electrónica, Escuela Superior de Ingenieros, 41092-Sevilla, Spain (e-mail: fbarrero@gte.esi.us.es). Publisher Item Identifier S 1063-6706(02)04833-6. I. INTRODUCTION T HE induction motor is a complex nonlinear system in which time-varying parameters entail an additional diffi- culty. Vector control methods have been proposed to simplify the speed control of induction motors so they can be controlled like a separately excited dc machine [4]. Indirect vector control methods decouple the motor current components by estimating the slip speed , which requires a proper knowledge of the rotor time constant, . Classical control systems like PI control have been used, to- gether with vector control methods, for the speed control of in- duction machines. The main drawbacks of the linear control ap- proach are the sensitivity in performance to the system parame- ters variations and inadequate rejection of external perturbations and load changes. To face these problems, variable-structure control based approaches, such as sliding-mode control (SLMC) [9], or fuzzy logic based control (FLBC), [12], [13], have been recently applied to the control of electrical drive systems. SLMC has been shown to be an effective way for control- ling electric drive systems. It is a robust control because the high-gain feedback control input cancels nonlinearities, uncer- tainty parameters, and external disturbances. It also offers a fast dynamic response, a stable control system and an easy hard- ware/software implementation. On the other hand, this control strategy offers some drawbacks associated with the large torque chattering that appears in a steady state, which may excite me- chanical resonance. Fuzzy-logic, first proposed by L. A. Zadeh, has recently re- ceived a great deal of attention. The easy way of defining a fuzzy controller by rules with an obvious physical meaning has helped to expand this control technique. When it is applied to con- trol nonlinear systems, this nonlinear control strategy has shown better results than classical controllers do. However, closed-loop system stability is difficult to be guaranteed. Recently, fuzzy sliding-mode controllers have been re- searched and applied to different systems, however, there are not many applications to an induction motor. In [14], a sliding- mode controller with an integral-operation switching surface was adopted to control the position of an induction servomotor drive in which a fuzzy neural network (FNN) sliding-mode was applied. The FNN is used to relax the requirement for the bounds of uncertainties estimating such uncertainties in real time. In [15], another fuzzy sliding-mode controller was proposed for position control. In this case, the fuzzy controller is added to the sliding-mode controller, but the stability of the system could not be guaranteed. 1063-6706/02$17.00 © 2002 IEEE