2024
DOI: 10.1109/tie.2023.3241412
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Low Complexity Model Predictive Flux Control Based on Discrete Space Vector Modulation and Optimal Switching Sequence for Induction Motors

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Cited by 11 publications
(3 citation statements)
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“…Also, the computational intensive control algorithm will affect the system performance in MPC. The existing computational burden reduction methods can generally be classified into two categories as reducing the complexity of prediction models and voltage vector (VV) preselection [5], [6], [8] - [11]. In [5] and [6], the torque and flux references are equivalently converted into a new flux reference or reference stator VV, thus reducing the complexity of prediction models.…”
Section: Introductionmentioning
confidence: 99%
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“…Also, the computational intensive control algorithm will affect the system performance in MPC. The existing computational burden reduction methods can generally be classified into two categories as reducing the complexity of prediction models and voltage vector (VV) preselection [5], [6], [8] - [11]. In [5] and [6], the torque and flux references are equivalently converted into a new flux reference or reference stator VV, thus reducing the complexity of prediction models.…”
Section: Introductionmentioning
confidence: 99%
“…First, the Heun's method was used to discretize (6) to estimate the stator and rotor flux at kth instant, and then to predict the parameters at (k+1)th instant to compensate for the one-step delay in the digital implementation [5], [30].…”
mentioning
confidence: 99%
“…MPC strategies directly control the switching states of power converters but the availability of the switching combinations for a power converter is limited, resulting in high current/torque harmonics in electric drives. To suppress these harmonics, multi-vector-based MPCs [20], [21] and modulated MPCs [22], [23] have been reported. The modulated MPCs also help to prevent variable switching frequency problems.…”
Section: Introductionmentioning
confidence: 99%