Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm

Uddin, Muslem; Mekhilef, Saad; Rivera, Marco; Rodríguez, José

doi:10.5370/jeet.2015.10.1.227

Cited by 19 publications

(7 citation statements)

References 41 publications

(46 reference statements)

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“…Particle swarm optimization based FCS-MPTC was proposed in [38] where the simple minimization of cost function was replaced with PSO in order to improve the steady state torque ripple. In [39], [40] optimized weighting factor was given in terms of rotor flux and reference voltage for matrix inverter fed IM. Here the author only studied the effect of weighting factor optimization for torque and ignore the switching losses in the inverter.…”

Section: Literature Review Of Mpcmentioning

confidence: 99%

Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making

et al. 2019

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Model predictive control (MPC) is the result of the latest advances in power electronics and modem control. It is regarded as one of the best techniques when it comes to handling of nonlinearities in the intrinsic model of induction motor (IM). Conventional MPC utilizes weighting factors in the objective function that are tuned after rigorous experimental work which can be improved by utilizing the more mature intelligent optimization techniques like NSGA-II etc. In this study, the weighting factor optimization for the conventional MPC control of IM based on NSGA-II with TOPSIS decision-making criteria is studied. A control algorithm is designed, and an experimental test setup is made to obtain the results of this intelligent MPC which are compared with conventional MPC based on some performance indices like torque and flux ripple, switching frequency loss etc.INDEX TERMS DTC, dynamic induction motor model, FOC, finite set control model non-dominated sorting genetic algorithm, predictive control, TOPSIS.

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Section: Literature Review Of Mpcmentioning

confidence: 99%

Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making

et al. 2019

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“…It has been applied to a variety of fields. Until now, many issues about MPC have been presented such as the cost function optimisation [21,22], the reduction of calculation time [23,24], the improvement of steady-state performance [25][26][27] and dynamic response [28], and the approach to fix the switching frequency [29]. This paper deals with one of the key points of any controller: namely, stable performance.…”

Section: Introductionmentioning

confidence: 99%

Ripple‐reduced model predictive direct power control for active front‐end power converters with extended switching vectors and time‐optimised control

Fang

Zhang²,

Feng

et al. 2016

IET Power Electronics

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Model predictive control (MPC) is an attractive technique for power electronics and drives. It requires no extra modulators and considers the non-linear nature of the power converter, so remarkable control performance can be achieved. However, since the conventional MPC scheme uses only one switching state during the whole control interval, ripples of the control variables are more evident than that of the classical modulator based techniques. This study proposed a ripple-reduced model predictive direct power control (RR-MPDPC) scheme for the grid-tied active front end using a fully field programmable gate array-based platform. The novelty of the proposed RR-MPDPC is that through extended switching vectors and time-optimised control, more freedoms and precise tracking possibility are realised in the predictive controller. The proposed control scheme is compared with the conventional MPDPC and the recently reported duty optimal MPDPC scheme (DutyOpt-MPDPC) through experimental data. Experimental results confirm that better performance is achieved using the proposed RR-MPDPC scheme.

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“…Then, the stator flux magnitude and torque at (k + 2)th instant can be predicted based on (18) and (19)…”

Section: Prediction On the Stationary Reference Framementioning

confidence: 99%

“…In [18], guidelines to determine suitable weighting factors based on an empirical procedure are demonstrated, but lack sufficient theoretical support. In [12,19], the principle of torque ripple minimisation is utilised to calculate the desired weighting factor online. However, the algorithm is computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

Simplified model predictive direct torque control method without weighting factors for permanent magnet synchronous generator‐based wind power system

Guo

Zhang

Yang

et al. 2017

IET Electric Power Applications

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Conventional model predictive direct torque control (MP-DTC) of permanent magnet synchronous generator (PMSG) suffers from weighing factor tuning work and relatively large calculation amount. This study proposes a simplified MP-DTC method without weighting factors for PMSG-based wind power system. First, the torque and stator flux magnitude are predicted on the stationary reference frame instead of on the synchronous rotating reference frame, hence reducing the calculation amount. Second, a new cost function based on the torque and the reactive torque is developed in this study. As the torque and the reactive torque have the same order of magnitude, the weighting factor which is needed in the conventional MP-DTC system is eliminated. Meanwhile, the stator current and stator flux magnitude can be controlled indirectly by controlling the torque and reactive torque simultaneously, which ensures the stability of the system. Besides, the robustness of the proposed strategy to unknown PMSG parameter variations is improved to a certain extent. The experimental results validate the effectiveness of the proposed method.

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Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm

Cited by 19 publications

References 41 publications

Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making

Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making

Ripple‐reduced model predictive direct power control for active front‐end power converters with extended switching vectors and time‐optimised control

Simplified model predictive direct torque control method without weighting factors for permanent magnet synchronous generator‐based wind power system

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