The paper deals with the motion control of an induction motor. Because the nonlinear state equations describing the dynamics of such a machine can be embedded into a linear model with the rotor speed ω as a varying parameter, advantage is taken of some recent results on the control of linear parameter-varying systems, thus ensuring stability independently of how the varying parameter changes in time within a compact set. The adopted control structure consists of a fast inner electric loop that controls the stator currents and an outer mechanical loop that generates the torque acting on the motor shaft. Of crucial importance is the design of the internal model controller for the current loop. In particular, it is proved that an algebraically equivalent electric motor model admits a Lyapunov function that, together with its Lyapunov derivative, is independent of ω and of all motor parameters. This result allows us to find an upper bound on the norm of the Youla-Kucera parameter that ensures robust stability against speed measurement errors. Simulations carried out on a benchmark motor model show that the adopted control strategy performs well. Copyright © 2014 John Wiley & Sons, Ltd.

### Robust linear parameter-varying control of induction motors

#### Abstract

The paper deals with the motion control of an induction motor. Because the nonlinear state equations describing the dynamics of such a machine can be embedded into a linear model with the rotor speed ω as a varying parameter, advantage is taken of some recent results on the control of linear parameter-varying systems, thus ensuring stability independently of how the varying parameter changes in time within a compact set. The adopted control structure consists of a fast inner electric loop that controls the stator currents and an outer mechanical loop that generates the torque acting on the motor shaft. Of crucial importance is the design of the internal model controller for the current loop. In particular, it is proved that an algebraically equivalent electric motor model admits a Lyapunov function that, together with its Lyapunov derivative, is independent of ω and of all motor parameters. This result allows us to find an upper bound on the norm of the Youla-Kucera parameter that ensures robust stability against speed measurement errors. Simulations carried out on a benchmark motor model show that the adopted control strategy performs well. Copyright © 2014 John Wiley & Sons, Ltd.
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2015
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Utilizza questo identificativo per citare o creare un link a questo documento: `https://hdl.handle.net/11390/1069566`
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