Predictive Torque and Flux Control Without Weighting Factors

Rojas, Christian A.; Rodríguez, José; Villarroel, Felipe; Espinoza, José; Silva, César; Trincado, M.

doi:10.1109/tie.2012.2206344

Cited by 366 publications

(233 citation statements)

References 37 publications

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“…In order to assign equal weight to the two dimensionally different state variables, the per-unit values are used as a rather simplistic way of dealing with a complex problem. For torque and flux predictive control found in the literature, the tuning of weights assigned to each variable is still a matter of research and no empirical tuning method exists to date [10,18,25]. The tuning of weights for flux and current state variables used here may also be treated in depth in a future work.…”

Section: Model Predictive Control Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Finite control set and modulated model predictive flux and current control for induction motor drives

Odhano

Formentini

Zanchetta

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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-The paper presents a new implementation of direct flux and current vector control of an induction motor drive using the techniques of model predictive control. The advantages offered by predictive control are used to enhance the dynamics of direct flux vector control. To minimize the problems of variable switching frequency inherent to finite control set predictive control, an alternative approach using pulse width modulation is studied for command execution as occurs in the so-called modulated model predictive control. A comparison between finite control set and modulated model predictive control is presented and the results are also compared with the control implementation through traditional proportional-integral regulators to highlight the advantages and drawbacks of predictive control based strategies. Apart from a greater harmonic content in stator currents, the predictive control can offers control dynamics comparable with proportional-integral control while maintaining immunity against machine parameter variations and excluding the need for controller tuning.

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Section: Model Predictive Control Formulationmentioning

confidence: 99%

“…Although this control type's use has majorly focused on converter control, the trend of its application for variable speed drives control is also on the rise [8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Finite control set and modulated model predictive flux and current control for induction motor drives

Odhano

Formentini

Zanchetta

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

View full text Add to dashboard Cite

show abstract

“…(25), (36) and (37) These equations are expressed the stator voltage and weighting factor relationship.…”

Section: Appendix Case 1: Ascending Slope Of the Torquementioning

confidence: 99%

“…Recently, a novel predictive two-level inverter fed induction motor control strategy with weighting factor look up table and divide control interval have been investigated in [35]. In [36], a ranking approach based multi-objective optimization has been proposed to replace the single cost function at the predictive horizon which allows the predictive control of torque and flux without weighting factors. To improve the speed control of IM, a continuous-time Poisson-Laguerre model based adaptive predictive controller has been applied successfully in [37] and different loss analysis at IM was investigated in [38].…”

Section: Introductionmentioning

confidence: 99%

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

Uddin¹,

Mekhilef²,

Rivera³

et al. 2015

Journal of Electrical Engineering and Technology

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-This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

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“…The FCS-MPC notion depends mainly on predicting the behavior of the controlled variables in future by using their discrete model. The development of rapid and powerful microprocessors makes the application of FCS-MPC in power electronics more attractive [13]. The control action in the future is achieved by a cost or objective function.…”

Section: Introductionmentioning

confidence: 99%

Modified Finite Control Set-Model Predictive Controller (MFCS-MPC) for quasi Z-Source Inverters based on a Current Observer

Bakeer¹,

Ismeil²,

Orabi³

2017

Journal of Power Electronics

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The Finite Control Set-Model Predictive Controller (FCS-MPC) for quasi Z-Source Inverters (qZSIs) is designed to reduce the number of sensors by proposing a current observer for the inductor current. Unlike the traditional FCS-MPC algorithm, the proposed model removes the inductor current sensor and observes the inductor current value based on the deposited prior optimized state as well as the capacitor voltage during this state. The proposed observer has been validated versus a typical MPC. Then, a comparative study between the proposed Modified Finite Control Set-Model Predictive Controller (MFCS-MPC) and a linear PID controller is provided under the same operating conditions. This study demonstrates that the dynamic response of the control objectives by MFCS-MPC is faster than that of the PID. On the other hand, the PID controller has a lower Total Harmonic Distortion (THD) when compared to the MFCS-MPC at the same average switching. Experimental results validate both methods using a DSP F28335.

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Predictive Torque and Flux Control Without Weighting Factors

Cited by 366 publications

References 37 publications

Finite control set and modulated model predictive flux and current control for induction motor drives

Finite control set and modulated model predictive flux and current control for induction motor drives

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

Modified Finite Control Set-Model Predictive Controller (MFCS-MPC) for quasi Z-Source Inverters based on a Current Observer

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