IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i9p2139-d1138442.html
   My bibliography  Save this article

State Feedback with Integral Control Circuit Design of DC-DC Buck-Boost Converter

Author

Listed:
  • Humam Al-Baidhani

    (Department of Electrical Engineering, Wright State University, Dayton, OH 45435, USA
    Department of Computer Techniques Engineering, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10011, Iraq)

  • Abdullah Sahib

    (Department of Electronic and Communication Technologies, Technical Institute, Al-Furat Al-Awsat Technical University, Najaf 54003, Iraq)

  • Marian K. Kazimierczuk

    (Department of Electrical Engineering, Wright State University, Dayton, OH 45435, USA)

Abstract

The pulse-with modulated (PWM) dc-dc buck-boost converter is a non-minimum phase system, which requires a proper control scheme to improve the transient response and provide constant output voltage during line and load variations. The pole placement technique has been proposed in the literature to control this type of power converter and achieve the desired response. However, the systematic design procedure of such control law using a low-cost electronic circuit has not been discussed. In this paper, the pole placement via state-feedback with an integral control scheme of inverting the PWM dc-dc buck-boost converter is introduced. The control law is developed based on the linearized power converter model in continuous conduction mode. A detailed design procedure is given to represent the control equation using a simple electronic circuit that is suitable for low-cost commercial applications. The mathematical model of the closed-loop power converter circuit is built and simulated using SIMULINK and Simscape Electrical in MATLAB. The closed-loop dc-dc buck-boost converter is tested under various operating conditions. It is confirmed that the proposed control scheme improves the power converter dynamics, tracks the reference signal, and maintains regulated output voltage during abrupt changes in input voltage and load current. The simulation results show that the line variation of 5 V and load variation of 2 A around the nominal operating point are rejected with a maximum percentage overshoot of 3.5% and a settling time of 5.5 ms.

Suggested Citation

  • Humam Al-Baidhani & Abdullah Sahib & Marian K. Kazimierczuk, 2023. "State Feedback with Integral Control Circuit Design of DC-DC Buck-Boost Converter," Mathematics, MDPI, vol. 11(9), pages 1-18, May.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2139-:d:1138442
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/9/2139/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/9/2139/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jorge A. Solsona & Sebastian Gomez Jorge & Claudio A. Busada, 2022. "Modeling and Nonlinear Control of dc–dc Converters for Microgrid Applications," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    2. Gabriel R. Broday & Luiz A. C. Lopes & Gilney Damm, 2022. "Exact Feedback Linearization of a Multi-Variable Controller for a Bi-Directional DC-DC Converter as Interface of an Energy Storage System," Energies, MDPI, vol. 15(21), pages 1-26, October.
    3. Peng Chen & Jilong Liu & Fei Xiao & Zhichao Zhu & Zhaojie Huang, 2021. "Lyapunov-Function-Based Feedback Linearization Control Strategy of Modular Multilevel Converter–Bidirectional DC–DC Converter for Vessel Integrated Power Systems," Energies, MDPI, vol. 14(15), pages 1-16, August.
    4. Rasool Kahani & Mohsin Jamil & M. Tariq Iqbal, 2022. "Direct Model Reference Adaptive Control of a Boost Converter for Voltage Regulation in Microgrids," Energies, MDPI, vol. 15(14), pages 1-19, July.
    5. Saeed Danyali & Omid Aghaei & Mohammadamin Shirkhani & Rahmat Aazami & Jafar Tavoosi & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    6. Jose A. Ruz-Hernandez & Larbi Djilali & Mario Antonio Ruz Canul & Moussa Boukhnifer & Edgar N. Sanchez, 2022. "Neural Inverse Optimal Control of a Regenerative Braking System for Electric Vehicles," Energies, MDPI, vol. 15(23), pages 1-19, November.
    7. Gabriel R. Broday & Gilney Damm & William Pasillas-Lépine & Luiz A. C. Lopes, 2021. "A Unified Controller for Multi-State Operation of the Bi-Directional Buck–Boost DC-DC Converter," Energies, MDPI, vol. 14(23), pages 1-21, November.
    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. Fazilah Hassan & Argyrios Zolotas & George Halikias, 2023. "New Insights on Robust Control of Tilting Trains with Combined Uncertainty and Performance Constraints," Mathematics, MDPI, vol. 11(14), pages 1-19, July.
    2. Abd Ur Rehman & Minsung Kim & Jin-Woo Jung, 2023. "State-Plane Trajectory-Based Duty Control of a Resonant Bidirectional DC/DC Converter with Balanced Capacitors Stress," Mathematics, MDPI, vol. 11(14), pages 1-17, July.

    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. Arun Kumar Udayakumar & Raghavendra Rajan Vijaya Raghavan & Mohamad Abou Houran & Rajvikram Madurai Elavarasan & Anushkannan Nedumaran Kalavathy & Eklas Hossain, 2023. "Three-Port Bi-Directional DC–DC Converter with Solar PV System Fed BLDC Motor Drive Using FPGA," Energies, MDPI, vol. 16(2), pages 1-21, January.
    2. Hammad Alnuman & Kuo-Hsien Hsia & Mohammadreza Askari Sepestanaki & Emad M. Ahmed & Saleh Mobayen & Ammar Armghan, 2023. "Design of Continuous Finite-Time Controller Based on Adaptive Tuning Approach for Disturbed Boost Converters," Mathematics, MDPI, vol. 11(7), pages 1-23, April.
    3. Marcin Kaminski & Tomasz Tarczewski, 2023. "Neural Network Applications in Electrical Drives—Trends in Control, Estimation, Diagnostics, and Construction," Energies, MDPI, vol. 16(11), pages 1-25, May.
    4. Weijun Hu & Jiale Quan & Xianlong Ma & Mostafa M. Salah & Ahmed Shaker, 2023. "Analytical Design of Optimal Model Predictive Control and Its Application in Small-Scale Helicopters," Mathematics, MDPI, vol. 11(8), pages 1-15, April.
    5. Gabriel R. Broday & Luiz A. C. Lopes & Gilney Damm, 2022. "Exact Feedback Linearization of a Multi-Variable Controller for a Bi-Directional DC-DC Converter as Interface of an Energy Storage System," Energies, MDPI, vol. 15(21), pages 1-26, October.
    6. Xiaohui Gao, 2022. "Monthly Wind Power Forecasting: Integrated Model Based on Grey Model and Machine Learning," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    7. Md Tahmid Hussain & Adil Sarwar & Mohd Tariq & Shabana Urooj & Amal BaQais & Md. Alamgir Hossain, 2023. "An Evaluation of ANN Algorithm Performance for MPPT Energy Harvesting in Solar PV Systems," Sustainability, MDPI, vol. 15(14), pages 1-36, July.
    8. Xin Xu & Ahmed Shaker & Marwa S. Salem, 2022. "Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    9. Myada Shadoul & Razzaqul Ahshan & Rashid S. AlAbri & Abdullah Al-Badi & Mohammed Albadi & Mohsin Jamil, 2022. "A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications," Energies, MDPI, vol. 15(22), pages 1-27, November.

    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:jmathe:v:11:y:2023:i:9:p:2139-:d:1138442. 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.