Robust speed control of induction motors: application to a benchmark example

Abstract

A non‐linear robust output feedback control is designed for a sixth‐order model of an induction motor. The control uses only measurement of the rotor position and stator currents. It contains two observers, a second‐order observer to estimate the rotor flux from the stator current and a third‐order high‐gain observer to estimate the rotor speed and acceleration from its position. The control is robust to uncertainties in the rotor and stator resistances, and a bounded time‐varying load torque. It guarantees that the speed tracking error can be made arbitrarily small by choice of certain design parameters. Moreover, when the speed reference and load torque and constant, it ensures asymptotic regulation. The controller is applied, via simulation, to a benchmark example. Copyright © 2000 John Wiley & Sons, Ltd.

An adaptive sliding mode observer for induction machines

“…A speed control algorithm with the proposed observer was simulated for an induction motor having the following constants [10]: L S = L R =0.47H, L M =0.44H; R S =8Ω and a nominal value of the rotor resistance R R =3 .6Ω (η =( R R /L R )=7 .7); P =2 ; and J =0 .05Nms 2 . The desired flux and speed values were 1.5Wb and 100rad/s respectively.…”

Control of induction motors: an adaptive passivity MIMO perspective

“…One scheme considers constant adaptive gains for the adaptive laws whereas the other has time-varying adaptive gains, which allows an improvement in the transient behaviour of the controlled system. Compared with other non-linear control schemes proposed in the literature such as sliding modes [1][2][3][4][10][11][12][13][14][15][16][17][18][19][20][21][22], we are in the presence of two simple and novel controllers. They have adaptive characteristics, are robust in the presence of load parameter variations and use simple proportional controllers in the rotor speed, rotor flux and stator current control loops.…”

“…However, all this techniques are based on complex control schemes that involve on line parameter estimation at every instant of time, state variable estimation (rotor flux estimation) and control strategy based on these estimations [13][14][15][16]. For example, we can cite different type of control techniques used to face this problem, such as robust discrete-time stabilization [17], nonlinear robust output feedback [18,19], state space H 1 [20], non-linear predictive control [21] and PI control [22].…”