By Fouad Giri
The complexity of AC motor keep watch over lies within the multivariable and nonlinear nature of AC laptop dynamics. contemporary developments up to speed conception now give the opportunity to house long-standing difficulties in AC vehicles keep watch over. this article expertly attracts on those advancements to use quite a lot of model-based regulate designmethods to numerous AC vehicles. Contributions from over thirty most sensible researchers clarify how glossy keep an eye on layout equipment can be utilized to accomplish tight pace law, optimum lively potency, and operation reliability and protection, through contemplating on-line kingdom variable estimation within the absence of mechanical sensors, strength issue correction, desktop flux optimization, fault detection and isolation, and fault tolerant keep watch over. Describing the full regulate strategy, either controller and observer designs are proven utilizing complex nonlinear equipment, balance and function are analysed utilizing strong options, together with implementation concerns utilizing electronic computing capability. different key good points: - Covers the most different types of AC automobiles together with triphase, multiphase, and doubly fed induction cars, wound rotor, everlasting magnet, and inside PM synchronous automobiles - Illustrates the usefulness of the complicated regulate tools through commercial purposes together with electrical autos, excessive pace trains, metal generators, and extra - contains distinct specialize in sensorless nonlinear observers, adaptive and strong nonlinear controllers, output-feedback controllers, fault detection and isolation algorithms, and fault tolerant controllers
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Extra resources for AC Electric Motors Control Advanced Design Techniques and Applications
Besides, some of their parameters are time varying and some of their state variables are not accessible to measurements. , Lubineau et al. 2000; Montanan et al. 2006; Traore et al. 2008; El Fadili et al. 2012a). These problems are generally dealt with using model-based control approaches, that is, the controller or the observer design relies upon a given model that is supposed to accurately describe the machine of interest. , Lubineau et al. 2000). Then, the obtained models turn out to be linear and of quite limited use.
To the ﬁctive MMF εo is associated a ﬁctive current, denoted i o , referred to homopolar. Accordingly, one has εo = n 2 i o . 12) the MMFs by the corresponding currents one gets the following relation between the three-phase current (i a , i b , i c ) (traversing n 1 turns) and the equivalent two-phase current (i d , i q ) (traversing n 2 turns): ⎡ ⎤ cos(ψ) id n 1 ⎢ ⎣ iq ⎦ = ⎣ − sin(ψ) n2 io K ⎡ o 2π 3 − 2π 3 cos ψ − − sin ψ Ko 4π 3 − 4π 3 cos ψ − − sin ψ Ko ⎤⎡ ⎤ ia ⎥⎣ ⎦ ⎦ ib . 13) As the ﬁctive current i o is not physically involved in the creation of the MMF, its orientation can be chosen arbitrarily.
Published 2013 by John Wiley & Sons, Ltd. 42 AC Electric Motors Control Arkkio et al. 1990; Bangura and Arkadan 1999). This method provides a very accurate description of the electromagnetic ﬁeld distribution in the machine. But, the proposed models are quite complex (large number of parameters) and computationally burdensome, which makes them of little interest for control design purpose. The second modelling method, referred to permeance network, consists of representing the machine magnetic circuit by an equivalent circuit diagram (Hecquet and Brochet 1998; Srairi et al.