A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control

Norambuena, Margarita; Rodríguez, José; Zhang, Zhenbin; Wang, Fengxiang; Garcia, Cristian; Kennel, Ralph

doi:10.1109/tpel.2018.2812833

Cited by 187 publications

(123 citation statements)

References 25 publications

(21 reference statements)

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“…The proposed PTC method for OEW-PMSM is initially tested in MATLAB/SIMULINK and compared with the classical PTC and SMPC. 38 The parameters of the PMSM are specified in Table 4. The empirical approach 22 is used for calculating the weighting factors of classical PTC method.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The dynamic behaviour of PMSM with classical, SMPC 38 Figure 12A, displays the performances (speed, electromagnetic torque and stator flux) of OEW-PMSM drive with classical PTC during the step changes in reference speed from 60 to 180 rad/s and then to 270 rad/s in forward motoring mode. The similar dynamic performances are also observed in SMPC 38 and proposed PTC during the same condition of step change in speeds, which is shown in Figure 12B,C respectively. In the same way, the reverse motoring of OEW-PMSM drive responses during the step changes in speeds from 60 to 180 rad/s and then to 270 rad/s with classical, SMPC 38 and proposed PTC are shown in Figure 13A-C respectively.…”

Section: Hardware Resultsmentioning

confidence: 99%

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Effective predictive torque control scheme for four‐level open‐end winding permanent magnet synchronous motor drive

Eshwar

Kumar

2020

Int Trans Electr Energ Syst

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The predictive torque control (PTC) scheme for four-level open-end winding permanent magnet synchronous motor drive (OEW-PMSM) is introduced in this article, owing to its simple and intuitive algorithm. However, the classical PTC-PMSM drive performance mainly depends on the weighting factors (WF) used in cost function (CF) and its selection is a cumbersome process. Hence, a new approach for eliminating these WFs is proposed for four-level PTC-OEW-PMSM drive without dropping its benefits in classical PTC method. The torque and flux objective errors are considered as two individual CFs and evaluated with all available voltage vectors (VVs). Then, the set of VVs corresponding to the ascending orders of CFs magnitudes is considered as separate VVs groups. The common VV present in both these VV groups represents the minimised torque error, flux error and treated as the optimal VV for the next control period. As a result, the monotonous flux WF tuning is no more required. The limited VVs strategy is also proposed for reducing the computational burden of PTC. The proposed four-level PTC method is initially tested in MATLAB/ SIMULINK and experimentally verified on PMSM drive. K E Y W O R D S four-level voltage source inverter and weighting factors, open-end winding, permanent magnet synchronous motor drive drive, predictive torque control 1 | INTRODUCTION Nowadays, studies on electric vehicles (EVs) are gaining extended attention in vehicular applications because of environmental and energy issues. 1,2 Due to the features of high power density and torque per weight ratio, good efficiency and simple structure, permanent magnet synchronous motor drive (PMSM) are popularly used in EVs. 3-5 Large electric and hybrid EV applications, like military vehicle and trucks, demand high power and which is achieved through the multi-level inverters (MLIs). The MLIs provide increased voltage levels on the output side and make better harmonic

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Hardware Resultsmentioning

confidence: 99%

Effective predictive torque control scheme for four‐level open‐end winding permanent magnet synchronous motor drive

Eshwar

Kumar

2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…In addition to the above mentioned, many other cases have been studied on HVAC [18][19][20][21][22][23][24][25][26][27]. In the present paper, a model predictive control (MPC) method has been used for controlling temperature and humidity which was previously only introduced for controlling temperature in [28][29][30]. Furthermore, different techniques have been employed to reduce the cost function [31][32][33][34][35].…”

Section: Related Workmentioning

confidence: 99%

Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control

et al. 2019

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Nowadays, by huge improvements in industrial control and the necessity of efficient energy consumption for buildings, unified managing systems are established to monitor and control mechanical equipment and energy usage. One of the main portions of the building management system (BMS) is the cooling and heating equipment called heating and ventilation and air-conditioning (HVAC). Based on temperature slow dynamic and presented uncertainty in modeling, a model predictive control (MPC) strategy to track both temperature and humidity is proposed in this study. The main goal of this study is to provide a framework to describe temperature and humidity elements required for dynamic modeling. Following that, by utilizing a predictive approach, a control strategy is obtained, which optimizes the tracking error of two interactional channel and performs the effort control by minimizing the optimization index. Other articles have mostly only had control over the temperature variable, but in our article, we tried to study the equations of temperature and humidity as well as their interference and according to the ASHRAE standard, both temperature and humidity controls must be accurate. The humidity was the novelty in our article. Simulation results proved the effectiveness of the proposed approach compared to the conventional proportional-integral controller. Evidently, the key idea behind the control objective is providing the comfort condition while consuming the least possible energy.

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“…The higher number of switch states contributes to the heavier computational burden. MPC was investigated for most power electronic converters [19][20][21][22]. However, there are some drawbacks associated with MPC, including a complicated weighting factor design and heavy computational burden.…”

Section: Introductionmentioning

confidence: 99%

“…In this control strategy, the complex weighting factor design process is avoided, and thus the computational burden is reduced. SMPC was first proposed in [22] for an induction motor. Only two control objectives were considered and the controller was not generalized.…”

Section: Introductionmentioning

confidence: 99%

Sequential Model Predictive Control of Three-Phase Direct Matrix Converter

Zhang

Norambuena

et al. 2019

Energies

Self Cite

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The matrix converter (MC) is a promising converter that performs the direct AC-to-AC conversion. Model predictive control (MPC) is a simple and powerful tool for power electronic converters, including the MC. However, weighting factor design and heavy computational burden impose significant challenges for this control strategy. This paper investigates the generalized sequential MPC (SMPC) for a three-phase direct MC. In this control strategy, each control objective has an individual cost function and these cost functions are evaluated sequentially based on priority. The complex weighting factor design process is not required. Compared with the standard MPC, the computation burden is reduced because only the pre-selected switch states are evaluated in the second and subsequent sequential cost functions. In addition, the prediction model computation for the following cost functions is also reduced. Specifying the priority for control objectives can be achieved. A comparative study with traditional MPC is carried out both in simulation and an experiment. Comparable control performance to the traditional MPC is achieved. This controller is suitable for the MC because of the reduced computational burden. Simulation and experimental results verify the effectiveness of the proposed strategy.

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A Very Simple Strategy for High-Quality Performance of AC Machines Using Model Predictive Control

Cited by 187 publications

References 25 publications

Effective predictive torque control scheme for four‐level open‐end winding permanent magnet synchronous motor drive

Effective predictive torque control scheme for four‐level open‐end winding permanent magnet synchronous motor drive

Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control

Sequential Model Predictive Control of Three-Phase Direct Matrix Converter

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