An Adaptive Controller for a General Class of Switched Reluctance Motor Models

Vedagarbha, P.; Dawson, D.M.; Rhodes, W.G.

doi:10.1016/s1474-6670(17)58112-4

Cited by 3 publications

(10 citation statements)

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“…Several analytical approximations for the flux linkage function have been reported in the literature. In this paper, we consider the ones made in the other work, [5][6][7][8] identified as models M1 to M4. An adaptive state observer is proposed for these four models, which are classified into two groups given as follows.…”

Section: Mathematical Models Of the Srmmentioning

confidence: 99%

“…Attention has been centered on permanent magnet synchronous motors (PMSMs) and induction motors, for which a large number of articles and monographs written by control specialists have appeared in the last few years (see, for instance, other works [1][2][3][4] and the references therein). Several publications have been reported in the control literature on the problem of model-based control of SRM (see, eg, other works [5][6][7][8] ). However, to the best of our knowledge, there have not been any developments on the practically important sensorless control problem, which is the topic of interest of this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Several analytical approximations to this relation have been reported, with no universal agreement on the prevalence of one over the other. For this reason, to widen our target audience, we present the proposed observer for four different mathematical models, namely, those reported in the other works, [5][6][7][8] for which full state-feedback model-based controller with guaranteed stability properties have been derived.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive state observers for sensorless control of switched reluctance motors

Ortega

Sarr

Bobtsov

et al. 2018

Intl J Robust & Nonlinear

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In this paper, we address the problem of state observation for sensorless control of switched reluctance motors (SRMs), that is, the regulation of the motor measuring only the voltage and the current of the electrical supply. Instrumental for the construction of the observer is the derivation of algebraic relations, which define regression models, between the unknown rotor flux and the measured quantities. With the knowledge of the flux, it is shown that the mechanical coordinates can be estimated with suitably tailored adaptive nonlinear observers. Replacing the observed states, in a certainty equivalent manner, with a full information stabilizing law completes the sensorless controller design. In contrast with other motors, there is no universally accepted mathematical model to describe the dynamics of SRMs. To widen our target audience, we present the results for four different mathematical models reported in the literature. Simulation results with a precise (finite element) model of the SRM are used to illustrate the performance of the proposed observer and sensorless control.

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Section: Mathematical Models Of the Srmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive state observers for sensorless control of switched reluctance motors

Ortega

Sarr

Bobtsov

et al. 2018

Intl J Robust & Nonlinear

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“…Following up the discussion in Section 3.3, we have tested our PID controller on a fully nonlinear model (1) where, for implementation purpose, we used the expression j .q; x/ D s arctan.ˇL j .Â/x j / (cf. [18]). The numerical simulations were carried out in SIMULINK TM of MATLAB TM with the parameters as showed in Tables I and II.…”

Section: Simulation Resultsmentioning

confidence: 99%

Robust passivity‐based control of switched‐reluctance motors

Lorı́a

Espinosa-Pérez

Chumacero

2014

Intl J Robust & Nonlinear

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We propose a state-feedback controller for switched-reluctance motors as a preliminary step toward the solution of the sensorless control problem (without measurement of rotor variables). We establish global exponential stability. Furthermore, our controller renders the closed-loop system robust to external disturbances, that is, input-to-state stable. Although there exist some works on sensorless control of switched-reluctance motors, these consist mainly of ad hoc solutions without theoretical foundation. The few theoretically validated results in the literature are established under more stringent conditions such as knowledge of the load torque.Ã corresponds to the phase-inductance variation relative to the rotor angular position, and N r denotes the number of poles.In Equations (1b) and (1c), R represents the stator resistance, J corresponds to the total rotor inertia, and Â and ! denote the angular position and velocity, respectively. The inputs are thethen, the map e ! C 1 > J >e 7 ! is passive; the passivity and robustness properties of (23) are conserved. Proposition 4.2 (GES by state feedback, with load compensation)The system (23) with v D Q C 1 is input-to-state-stable with respect to 1 , and the map 1 7 ! e ! C 1 > J >e is output-strictly passive. Moreover, if 1 Á 0, that is, if v D Q , then the origin .e ; e ! ; Q / D .0; 0; 0/ of (23) is globally exponentially stable for appropriate values of the gains k p , k d , and k i .

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“…

In this paper it is shown that the controller presented in (Espinosa-Perez et al, 2004) for Switched Reluctance Motors can be improved, preserving its passivity-based structure, by eliminating the necessity of solving a transcendental equation to compute the desired behavior of stator currents when nonlinear magnetic circuits are considered in the machine model. This advantage in the controller design is obtained by considering the alternative expression for the nonlinear relationship between fluxes and currents reported in (Vedagarbha et al, 1997) that, as well as the previously used, includes the saturation phenomenon presented in the motor windings. Regarding the controller structure, the main implication of introducing this modification lies in the fact that it states the possibility of implementing a control law for a general class of models for this kind of motors.

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confidence: 99%