Nonlinear predictive controller design of PMSM with field weakening performance

Graf, Marcel; Buchta, Ludek; Pohl, Lukas

doi:10.1109/iecon.2013.6699608

Cited by 6 publications

(7 citation statements)

References 21 publications

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“…The equations for the matrices describing this affine PMSM model are the basis for the discretisation step. As discussed later, simulations showed that discretisation with Euler approximation is not sufficient, which is in accordance with [11, 12]. The system was discretised with a third‐order Picard Iteration [13] to provide remedy to that problem.…”

Section: Modelling Of the Pmsmmentioning

confidence: 61%

Non‐linear MPC for winding loss optimised torque control of anisotropic PMSM

Schnurr

Hohmann

Kolb

2019

J. eng.

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Section: Modelling Of the Pmsmmentioning

confidence: 61%

Non‐linear MPC for winding loss optimised torque control of anisotropic PMSM

Schnurr

Hohmann

Kolb

2019

J. eng.

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“…2) Discretization: In accordance with [31] and [32] simulations show that a discretization with Euler Approximation is not reasonable for higher angular velocities ω el . The system was discretized with a third order Picard Iteration [33].…”

Section: B Affine State Space Modelmentioning

confidence: 78%

Novel Lexicographic MPC for Loss Optimized Torque Control of Nonlinear PMSM

Schnurr

Hohmann

Kolb

2018

2018 IEEE Conference on Control Technology and Applications (CCTA)

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In electrical drive applications torque tracking is conflicting with the subsidiary goal of loss minimization. In this Paper a lexicographic optimization is proposed to solve this conflict by stringent prioritization. A novel model predictive control (MPC) with a single objective function is presented which is proved to be equal to lexicographic optimization in steady state. The loss weighting factor does not affect the steady state tracking offset and no current set points are needed. Results are confirmed by a simulation with an experimental validated machine model. The torque of an anisotropic permanent magnet synchronous machine (PMSM) fed by a voltage source inverter (VSI) is controlled with minimal ohmic losses. The optimization under input constraints is done using the projected fast gradient method (PFGM).

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“…Obviously, an accurate discrete‐time model of the system is required for NMPC. Assuming i d , i q , and ω as the system states, the nonlinear model can be rewritten in discrete time by using Forward‐Euler method as

i_{d} ((), k + 1) = i_{d} ((), k) + \frac{T_{s}}{L_{d}} ((), u_{d} ((), k) + L_{q} ω ((), k) i_{q} ((), k) - {Ri}_{d} ((), k)),

\begin{matrix} lefttrue \\ i_{q} (k + 1) = i_{q} (k) + \frac{T_{s}}{L_{q}} (u_{q} (k) - L_{d} ω (k) i_{d} (k) - {italicRi}_{q} (k), \\ - λω (k)) \end{matrix}

ω ((), k + 1) = ω ((), k) + \frac{T_{s} n_{p}}{K} ((), T_{e} ((), k) - T_{l}) .

…”

Section: Nonlinear Model Predictive Direct Speed Controlmentioning

confidence: 99%

“…Obviously, an accurate discrete-time model of the system is required for NMPC. Assuming i d , i q , and ω as the system states, the nonlinear model can be rewritten in discrete time by using Forward-Euler method 42 as…”

Section: Discretized Model Of the Pmsmmentioning

confidence: 99%

An improved nonlinear model predictive direct speed control of permanent magnet synchronous motors

Younesi

Tohidi

Feyzi

et al. 2018

Int Trans Electr Energ Syst

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Summary Field‐oriented control (FOC) is one of the most effective techniques widely used in industry for speed control of permanent magnet synchronous motor. However, the main drawback of such linear controller with cascade structure is its limited bandwidth to avoid large overshoots and ringing. This problem significantly increases the switching frequency. To overcome this problem, this paper proposes a novel nonlinear model predictive control (NMPC) scheme for direct speed control of the permanent magnet synchronous motor to minimize the inverter switching frequency. The proposed NMPC suggests different sampling times in the prediction process to increase the prediction horizon. It also presents an incremental algorithm to reduce the computational time, rendering it suitable for real‐time applications. The performance of the proposed NMPC method is compared with an optimum FOC scheme via simulations performed by MATLAB/Simulink software. The results show that the proposed method provides improved speed tracking performance as well as lower electromagnetic torque ripple. In addition, the inverter average switching frequency with the proposed control approach is almost 10 times lower than that with the FOC approach.

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Nonlinear predictive controller design of PMSM with field weakening performance

Cited by 6 publications

References 21 publications

Non‐linear MPC for winding loss optimised torque control of anisotropic PMSM

Non‐linear MPC for winding loss optimised torque control of anisotropic PMSM

Novel Lexicographic MPC for Loss Optimized Torque Control of Nonlinear PMSM

An improved nonlinear model predictive direct speed control of permanent magnet synchronous motors

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