Hybrid control for speed sensorless induction motor drive

The dynamic response of a hybrid-controlled speed sensorless induction moto r (IM) drive is introduced in this paper. First, an adaptive observation sy stem, which comprises speed and flux observers, is derived on the basis of model reference adaptive system (MRAS) theory, The speed observation system is implemented using a digital signal processor (DSP) with a high sampling rate to make it possible to achieve good dynamics. Next, based on the prin ciple of computed torque control, a computed torque controller using the es timated speed signal is developed. Moreover, to relax the requirement of th e lumped uncertainty in the design of a computed torque controller, a recur rent fuzzy neural network (RFNN) uncertainty observer is utilized to adapt the lumped uncertainty on line. Furthermore, based on the Lyapunov stabilit y a hybrid control system, which combines the computed torque controller, t he RFNN uncertainty observer and a compensated controller, is proposed to c ontrol the rotor speed of the sensorless IM drive, The computed torque cont roller with RFNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximat ion error of the uncertainty observer instead of increasing the rules of th e RFNN, Finally, the effectiveness of the proposed observation and control systems is verified by simulated and experimental results.