IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1193-d328757.html
   My bibliography  Save this article

Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches

Author

Listed:
  • Karol Wróbel

    (Department of Electrical Drives and Measurements, Wrocław University of Science and Technology, 50-370 Wrocław, Poland)

  • Piotr Serkies

    (Department of Electrical Drives and Measurements, Wrocław University of Science and Technology, 50-370 Wrocław, Poland)

  • Krzysztof Szabat

    (Department of Electrical Drives and Measurements, Wrocław University of Science and Technology, 50-370 Wrocław, Poland)

Abstract

In the paper a comparative study of the two control structures based on MPC (Model Predictive Control) for an electrical drive system with an induction motor are presented. As opposed to the classical approach, in which DFOC (Direct Field Oriented Control) with four controllers is considered, in the current study only one MPC controller is utilized. The proposed control structures have a cascade free structure that consists of a vector of electromagnetic (torque, flux) and mechanical (speed) states of the system. The first investigated framework is based on the finite-set MPC. A short horizon predictive window is selected. The continuous set MPC is used in the second framework. In this case the predictive horizon contains several samples. The computational complexity of the algorithm is reduced by applying its explicit version. Different implementation aspects of both MPC structures, for instance the model used in prediction, complexity of the control algorithms, and their properties together with the noise level are analyzed. The effectiveness of the proposed approach is validated by some experimental tests.

Suggested Citation

  • Karol Wróbel & Piotr Serkies & Krzysztof Szabat, 2020. "Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches," Energies, MDPI, vol. 13(5), pages 1-15, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1193-:d:328757
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1193/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/5/1193/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ibrahim Mohd Alsofyani & Kyo-Beum Lee, 2019. "Improved Deadbeat FC-MPC Based on the Discrete Space Vector Modulation Method with Efficient Computation for a Grid-Connected Three-Level Inverter System," Energies, MDPI, vol. 12(16), pages 1-18, August.
    2. Tao Lei & Weiwei Tan & Guangsi Chen & Delin Kong, 2018. "A Novel Robust Model Predictive Controller for Aerospace Three-Phase PWM Rectifiers," Energies, MDPI, vol. 11(9), pages 1-22, September.
    3. Pedro Gonçalves & Sérgio Cruz & André Mendes, 2019. "Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview," Energies, MDPI, vol. 12(24), pages 1-42, December.
    4. Fengxiang Wang & Zhenbin Zhang & Xuezhu Mei & José Rodríguez & Ralph Kennel, 2018. "Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control," Energies, MDPI, vol. 11(1), pages 1-13, January.
    5. GuangQing Bao & WuGang Qi & Ting He, 2020. "Direct Torque Control of PMSM with Modified Finite Set Model Predictive Control," Energies, MDPI, vol. 13(1), pages 1-16, January.
    6. Wei Wang & Zhixiang Lu & Wei Hua & Zheng Wang & Ming Cheng, 2019. "Simplified Model Predictive Current Control of Primary Permanent-Magnet Linear Motor Traction Systems for Subway Applications," Energies, MDPI, vol. 12(21), pages 1-17, October.
    7. Crestian Almazan Agustin & Jen-te Yu & Cheng-Kai Lin & Xiang-Yong Fu, 2019. "A Modulated Model Predictive Current Controller for Interior Permanent-Magnet Synchronous Motors," Energies, MDPI, vol. 12(15), pages 1-20, July.
    8. Shuang Feng & Chaofan Wei & Jiaxing Lei, 2019. "Reduction of Prediction Errors for the Matrix Converter with an Improved Model Predictive Control," Energies, MDPI, vol. 12(15), pages 1-20, August.
    9. Vijay Kumar Singh & Ravi Nath Tripathi & Tsuyoshi Hanamoto, 2020. "FPGA-Based Implementation of Finite Set-MPC for a VSI System Using XSG-Based Modeling," Energies, MDPI, vol. 13(1), pages 1-18, January.
    10. Osvaldo Gonzalez & Magno Ayala & Jesus Doval-Gandoy & Jorge Rodas & Raul Gregor & Marco Rivera, 2019. "Predictive-Fixed Switching Current Control Strategy Applied to Six-Phase Induction Machine," Energies, MDPI, vol. 12(12), pages 1-14, June.
    11. Lihui Wang & Guojun Tan & Jie Meng, 2019. "Research on Model Predictive Control of IPMSM Based on Adaline Neural Network Parameter Identification," Energies, MDPI, vol. 12(24), pages 1-16, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shujing Li & Zewen Wang & Yan Yan & Tingna Shi, 2021. "Finite Set Model Predictive Control of a Dual-Motor Torque Synchronization System Fed by an Indirect Matrix Converter," Energies, MDPI, vol. 14(5), pages 1-17, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jaime A. Rohten & David N. Dewar & Pericle Zanchetta & Andrea Formentini & Javier A. Muñoz & Carlos R. Baier & José J. Silva, 2021. "Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency," Energies, MDPI, vol. 14(2), pages 1-16, January.
    2. Habib Benbouhenni & Nicu Bizon, 2021. "Improved Rotor Flux and Torque Control Based on the Third-Order Sliding Mode Scheme Applied to the Asynchronous Generator for the Single-Rotor Wind Turbine," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    3. Carlos Romero & Larizza Delorme & Osvaldo Gonzalez & Magno Ayala & Jorge Rodas & Raul Gregor, 2021. "Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines," Energies, MDPI, vol. 14(13), pages 1-15, June.
    4. Thyago Estrabis & Gabriel Gentil & Raymundo Cordero, 2021. "Development of a Resolver-to-Digital Converter Based on Second-Order Difference Generalized Predictive Control," Energies, MDPI, vol. 14(2), pages 1-22, January.
    5. Sergio Toledo & Edgar Maqueda & Marco Rivera & Raúl Gregor & Pat Wheeler & Carlos Romero, 2020. "Improved Predictive Control in Multi-Modular Matrix Converter for Six-Phase Generation Systems," Energies, MDPI, vol. 13(10), pages 1-13, May.
    6. Pedro Gonçalves & Sérgio Cruz & André Mendes, 2019. "Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview," Energies, MDPI, vol. 12(24), pages 1-42, December.
    7. Sofiane Bacha & Ramzi Saadi & Mohamed Yacine Ayad & Mohamed Sahraoui & Khaled Laadjal & Antonio J. Marques Cardoso, 2023. "Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach," Energies, MDPI, vol. 16(5), pages 1-26, March.
    8. Marwa Ben Slimene & Mohamed Arbi Khlifi, 2022. "Investigation on the Effects of Magnetic Saturation in Six-Phase Induction Machines with and without Cross Saturation of the Main Flux Path," Energies, MDPI, vol. 15(24), pages 1-18, December.
    9. Kodkin Vladimir & Anikin Alexander, 2021. "On the Physical Nature of Frequency Control Problems of Induction Motor Drives," Energies, MDPI, vol. 14(14), pages 1-15, July.
    10. Omar Sandre Hernandez & Jorge S. Cervantes-Rojas & Jesus P. Ordaz Oliver & Carlos Cuvas Castillo, 2021. "Stator Fixed Deadbeat Predictive Torque and Flux Control of a PMSM Drive with Modulated Duty Cycle," Energies, MDPI, vol. 14(10), pages 1-15, May.
    11. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    12. Ahmed G. Mahmoud A. Aziz & Almoataz Y. Abdelaziz & Ziad M. Ali & Ahmed A. Zaki Diab, 2023. "A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques," Energies, MDPI, vol. 16(6), pages 1-32, March.
    13. Zhanqing Zhou & Xin Gu & Zhiqiang Wang & Guozheng Zhang & Qiang Geng, 2019. "An Improved Torque Control Strategy of PMSM Drive Considering On-Line MTPA Operation," Energies, MDPI, vol. 12(15), pages 1-17, July.
    14. Hui Yang & Rui Tu & Ke Wang & Jiaxing Lei & Wenjia Wang & Shuang Feng & Chaofan Wei, 2019. "A Hybrid Predictive Control for a Current Source Converter in an Aircraft DC Microgrid," Energies, MDPI, vol. 12(21), pages 1-14, October.
    15. Tadeusz Białoń & Roman Niestrój & Jarosław Michalak & Marian Pasko, 2021. "Induction Motor PI Observer with Reduced-Order Integrating Unit," Energies, MDPI, vol. 14(16), pages 1-12, August.
    16. Chi Zhang & Binyue Xu & Jasronita Jasni & Mohd Amran Mohd Radzi & Norhafiz Azis & Qi Zhang, 2023. "Three Voltage Vector Duty Cycle Optimization Strategy of the Permanent Magnet Synchronous Motor Driving System for New Energy Electric Vehicles Based on Finite Set Model Predictive Control," Energies, MDPI, vol. 16(6), pages 1-18, March.
    17. Cheng-Kai Lin & Jen-te Yu & Hao-Qun Huang & Jyun-Ting Wang & Hsing-Cheng Yu & Yen-Shin Lai, 2018. "A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems," Energies, MDPI, vol. 11(7), pages 1-29, July.
    18. Erhab Youssef & Pedro B. C. Costa & Sonia F. Pinto & Amr Amin & Adel A. El Samahy, 2020. "Direct Power Control of a Single Stage Current Source Inverter Grid-Tied PV System," Energies, MDPI, vol. 13(12), pages 1-20, June.
    19. Wei Wang & Zhixiang Lu, 2020. "Analysis of Model Predictive Current-Controlled Permanent Magnet Synchronous Motor Drives with Inaccurate DC Bus Voltage Measurement," Energies, MDPI, vol. 13(2), pages 1-15, January.
    20. Yuzhe Zhang & Xiaodong Liu & Haitao Li & Zhenbin Zhang, 2023. "A Model Independent Predictive Control of PMSG Wind Turbine Systems with a New Mechanism to Update Variables," Energies, MDPI, vol. 16(9), pages 1-15, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1193-:d:328757. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.