Predictive Control Applied to Matrix Converters: A Systematic Literature Review
Abstract
:1. Introduction
2. Background
3. The Systematic Literature Review Method
3.1. Scope of the Review
- RQ1: Which variants of model-based predictive control are used with matrix converters?
- RQ2: What matrix converter topologies handle predictive control?
3.2. Search for Primary Studies
- Matrix converter.
- Predictive control.
- IEEE Xplore (http://ieeexplore.ieee.org/), accessed on 13 July 2020,
- SCOPUS (https://www.scopus.com/), accessed on 13 July 2020,
- IET Digital Library (http://digital-library.theiet.org/), accessed on 13 July 2020, and
- Web of Knowledge (http://www.webofknowledge.com), accessed on 13 July 2020.
- Science Direct (http://www.sciencedirect.com/), accessed on 13 July 2020,
- Wiley InterScience (http://onlinelibrary.wiley.com/), accessed on 13 July 2020, and
- Springer link (http://link.springer.com/), accessed on 13 July 2020.
Algorithm 1: Search strings generation |
|
3.3. Study Selection and Data Extraction
3.3.1. Inclusion Criteria
- IC1: The study is published in Q1/Q2 Journals or in peer-reviewed conference proceedings.
- IC2: The study is written in English.
3.3.2. Exclusion Criteria
- EC1: Duplicate studies found in different databases are excluded (i.e., just one is considered).
- EC2: Only primary studies are considered; if the study is a review, it is excluded.
- EC3: The title explicitly mentions that the topic is not related to matrix converter or predictive control.
- EC4: The study’s lack of consideration of predictive control in a matrix converter is made clear in the abstract.
- EC5: If there are different iterations of the same study, the less thorough are disregarded.
- EC6: Full text read reveals the study does not refer to predictive control applied to a matrix converter.
3.3.3. Quality Assessment
- a.
- How the results are presented:
- Experimental results (0.6 pts).
- Simulation results (0.4 pts).
- Not presented (0 pts).
- b.
- Clarity in the topology. For a good level of clarity, the article should describe:
- Power circuit (0.5 pts).
- Knowledge of the valid states (0.2 pts)
- Relationship between input and output (0.3 pts)
A totally clear topology will be assigned 1 pt. - c.
- Accuracy in predictive control description. For complete clarity of predictive control application, the study must include:
- Control scheme (0.2 pts).
- Prediction model (0.5 pts).
- Cost function (0.3 pts).
3.3.4. Data Extraction
3.4. Synthesis of the Extracted Data
4. Model Predictive Control Applied to Matrix Converters
4.1. Basic Principles of MPC
- The system’s discretized model is used to predict how the variables of interest will behave in the future up to a given horizon. The system’s discretized state-space equations, for instance, could be used as follows:
- The intended control performance is then used to define a cost function, g. The reference and predicted values of the control variables are included in this cost function, together with the actuation.
- Finally, optimal actuation is obtained to solve the optimisation problem; the result that minimises g is applied by the controller.
4.2. Predictive Current Control
Algorithm 2: Predictive current control in DMC |
1. Initialize , 2. Measure , , 3. From j = 1 to 27 4. Calculate using (Equation (4)) 5. Calculate the predicted current using Equation (10) 6. Calculate the cost function using Equation (11) 7. if then 8. , 9. end if 10. end for 11. Apply the optimal state |
4.2.1. Predictive Current Control with Reactive Power Minimization
4.2.2. Predictive Current Control with Imposed Input Current
4.2.3. Predictive Current Control with Input Resonances Mitigation
4.2.4. Predictive Current Control with Common-Mode Voltage
4.2.5. Predictive Current Control with Switching Losses Reduction
4.3. Predictive Torque and Flux Control
4.4. Predictive Voltage Control
4.5. Predictive Power Control
4.6. Predictive Position and Speed Control
5. Matrix Converter Topologies Using Model Predictive Control
5.1. Direct Matrix Converter and Its Derivations
5.1.1. Single-Phase Matrix Converter
5.1.2. Multi-Phase Direct Matrix Converters
5.1.3. Quasi-Z-Source Matrix Converter
5.1.4. Multi-Modular Matrix Converter
5.1.5. Modular Multilevel Matrix Converter
5.2. Indirect Matrix Converter and Its Derivatives
5.2.1. A Four-Leg IMC
5.2.2. Three-Level Indirect Matrix Converter (3L-IMC)
5.2.3. Third-Harmonic Injection Two-Stage Matrix Converter
5.2.4. Sparse Matrix Converter
5.2.5. Matrix-Converter-Based Solid State Transformer
5.2.6. Hybrid Indirect Matrix Converter
5.2.7. Multi-Drive Indirect Matrix Converter
6. New Trends on Model Predictive Control Applied to Matrix Converters
6.1. Variable Switching Frequency
6.2. Avoiding the Use of Weighting Factors
6.3. Reducing Computational Burden
6.4. Fault Detection Using MPC
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
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string1 | string2 | |
---|---|---|
1 | Matrix Converter | Predictive Control |
2 | Cycloconverter | MPC |
3 | Direct ac |
Application | Citations | |
---|---|---|
1 | Motor drive | [51,104,132] |
2 | Isolated load feeder | [31,86,90,133,134] |
3 | Grid connected generation systems | [117] |
4 | Active filter | [33] |
5 | Non-linear load feeder | [122] |
Application | Citations | |
---|---|---|
1 | Current control | [18,90,135] |
2 | Torque and flux control | [101,102,114] |
3 | Voltage control | [117] |
4 | Position control | [130] |
5 | Power control | [128] |
Technique | Weight Factor | Modulation | Switching Frequency |
---|---|---|---|
Basic predictive control [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46] | Not needed | Not needed | Variable |
Predictive control with reactive power minimization [47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73] | Needed | Not needed | Variable |
Predictive control with imposed input current | Needed | Not needed | Variable |
Modulated predictive control [40,132,139] | Not needed | Needed | Fixed |
Modulated predictive control with input reactive power minimization [57,137,147] | Not needed | Needed | Fixed |
Modulated predictive control with imposed sinusoidal input current [136,145,146] | Not needed | Needed | Fixed |
Multi-objective ranking-based predictive control [112] | Not needed | Not needed | Variable |
Sequential predictive control [150] | Not needed | Not Needed | Variable |
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Toledo, S.; Caballero, D.; Maqueda, E.; Cáceres, J.J.; Rivera, M.; Gregor, R.; Wheeler, P. Predictive Control Applied to Matrix Converters: A Systematic Literature Review. Energies 2022, 15, 7801. https://doi.org/10.3390/en15207801
Toledo S, Caballero D, Maqueda E, Cáceres JJ, Rivera M, Gregor R, Wheeler P. Predictive Control Applied to Matrix Converters: A Systematic Literature Review. Energies. 2022; 15(20):7801. https://doi.org/10.3390/en15207801
Chicago/Turabian StyleToledo, Sergio, David Caballero, Edgar Maqueda, Juan J. Cáceres, Marco Rivera, Raúl Gregor, and Patrick Wheeler. 2022. "Predictive Control Applied to Matrix Converters: A Systematic Literature Review" Energies 15, no. 20: 7801. https://doi.org/10.3390/en15207801
APA StyleToledo, S., Caballero, D., Maqueda, E., Cáceres, J. J., Rivera, M., Gregor, R., & Wheeler, P. (2022). Predictive Control Applied to Matrix Converters: A Systematic Literature Review. Energies, 15(20), 7801. https://doi.org/10.3390/en15207801