Model Predictive Control: A Review of Its Applications in Power Electronics

Vázquez, Sergio; Leon, Jose I.; Franquelo, Leopoldo G.; Rodríguez, José; Young, Héctor; Márquez, Antonio J.; Zanchetta, Pericle

doi:10.1109/mie.2013.2290138

Cited by 946 publications

(381 citation statements)

References 46 publications

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“…Furthermore, the MPC does not require tuning of PI controller gains. As with other applications of MPC in power electronics and drives [6], analytical expressions cannot be derived to prove MPC's robustness against parameter variations. Simulations and experiments performed with detuned parameters could be used to ascertain the degree of immunity to parameter deviations.…”

Section: Resultsmentioning

confidence: 99%

“…After its conception in the early '60s and successful implementation for industrial process control ever since, the model predictive control [1][2][3][4][5] has gained popularity in the recent past for its application in power electronics control [6][7][8]19] that has opened a host of possibilities for the control of power converters. 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%

“…Current research trends on the application of model predictive control (MPC) in power electronic systems focus on the following four macro areas: grid-connected converters, power converters supplying R-L loads, inverters with L-C output filters, and high performance motor drives [6]. In the area of motor drives, MPC has been very successfully employed for predictive torque control (PTC) [9,10,13,14] and predictive current control (PCC) [13], and predictive flux control (PFC) [11] and speed control [15] of induction motor drives.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

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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show abstract

“…Model predictive control (MPC) has appeared as a promising alternative to classical control algorithms with pulse width modulation (PWM) for power converters control [18,19].…”

Section: Predictive Current Controlmentioning

confidence: 99%

Model predictive control of multilevel cascaded converter with boosting capability – experimental results

Wiatr

Kryński

2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. The main goal of this paper is to present a five-level converter with the feature of output voltage boosting capability. Thanks to its modular construction and single DC source usage, 5LCHB converter becomes an important alternative for two-level converters operating with DC-DC converters that use bulky inductors. Furthermore, model predictive control (MPC) method is presented, which allows for boosting output voltage of presented converter while providing three-phase load current control and flying capacitor voltage stabilization. The last section describes a 5kVA laboratory model of five-level hybrid converter interfacing RL load and shows experimental results confirming theoretical analysis derived in previous sections. By applying modifications to classic multilevel converter topologies, another branch called hybrid converters was created.Hybrid converters integrate more than one converter topology into one. Each new topology has its own advantages and drawbacks and suits a certain application.The following examples of hybrid converter topologies can be listed out: -5L-HNPC -cascaded connection of 3L-NPC converter[11], -ANCP-5L -3L-NPC converter connected with 3L-FC converter [12], -3L-NPC connected with H-bridge [13], -5L-MLC 2 -[14] This paper presents an investigation of a novel hybrid converter topology -five-level cascaded H-bridge converter (5LCHB) with only one DC source and model predictive controller (MPC). According to [1,15] this converter brings the following features:-generation of boosted output voltage, -good quality of output waveform with low THD, -fast response to reference current change. Utilization of the model predictive controller (MPC) for 5LCHB converter was tested in [1,15]. The advantages of MPC control can be summed up as follows:-simple solution for multilevel converter compared to other control strategies, -elimination of PWM modulator, -simple implementation of capacitor voltage balancing. Among the disadvantages of the MPC control we may list:-requirement of fast processor for on-line optimization, -the knowledge of the load parameters. Previous publication concerning 5LCHB converter with MPC control used only simulation model [1,[15][16][17]. This work examines 5 kVA laboratory model of 5LCHB with the MPC control.

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“…Owing to the fast response, robust operation and relatively low tuning effort, MPC is gaining acceptance in other areas as well, with varying success (Vazquez et al, 2014). MPC predicts the optimal future control Composite model reference adaptive control for an unmanned underwater vehicle profile using a mathematical model of the system and current states.…”

Section: Introductionmentioning

confidence: 99%

Composite model reference adaptive control for an unmanned underwater vehicle

Makavita¹,

Nguyen²,

Ranmuthugala³

et al. 2015

uw tech: int j soc uw tech

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The control of unmanned underwater vehicles (UUVs) is challenging due to the non-linear and time-varying nature of the hydrodynamic forces from the surrounding fluid. In addition, the presence of external disturbances makes the control even more difficult. Model reference adaptive control (MRAC) is an adaptive control technique that performs well in such situations, while the improved composite/combined model reference adaptive control (CMRAC) is capable of better transient performance. However, the latter is yet to be used in UUV controls. Thus, this paper tests the suitability of CMRAC in UUV applications using validated simulation models and compares its performance against the standard MRAC. Several test scenarios have been considered including initial operation, external disturbance and thruster failure. Simulation results show that CMRAC offers better tracking, faster disturbance rejection and quick recovery from thruster failure compared to MRAC. In addition, CMRAC is more robust against parameter uncertainties and thus the control signal shows fewer oscillations, which in turn reduces the probability of actuator damage.

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Model Predictive Control: A Review of Its Applications in Power Electronics

Cited by 946 publications

References 46 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

Model predictive control of multilevel cascaded converter with boosting capability – experimental results

Composite model reference adaptive control for an unmanned underwater vehicle

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