IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7566-d941568.html
   My bibliography  Save this article

Minimum Energy Control of Quadrotor UAV: Synthesis and Performance Analysis of Control System with Neurobiologically Inspired Intelligent Controller (BELBIC)

Author

Listed:
  • Wojciech Giernacki

    (Faculty of Automatic Control, Robotics and Electrical Engineering, Institute of Robotics and Machine Intelligence, Poznan University of Technology, ul. Piotrowo 3a, 60-965 Poznan, Poland)

Abstract

There is a strong trend in the development of control systems for multi-rotor unmanned aerial vehicles (UAVs), where minimization of a control signal effort is conducted to extend the flight time. The aim of this article is to shed light on the problem of shaping control signals in terms of energy-optimal flights. The synthesis of a UAV autonomous control system with a brain emotional learning based intelligent controller (BELBIC) is presented. The BELBIC, based on information from the feedback loop of the reference signal tracking system, shows a high learning ability to develop an appropriate control action with low computational complexity. This extends the capabilities of commonly used fixed-value proportional–integral–derivative controllers in a simple but efficient manner. The problem of controller tuning is treated here as a problem of optimization of the cost function expressing control signal effort and maximum precision flight. The article introduces several techniques (bio-inspired metaheuristics) that allow for quick self-tuning of the controller parameters. The performance of the system is comprehensively analyzed based on results of the experiments conducted for the quadrotor model.

Suggested Citation

  • Wojciech Giernacki, 2022. "Minimum Energy Control of Quadrotor UAV: Synthesis and Performance Analysis of Control System with Neurobiologically Inspired Intelligent Controller (BELBIC)," Energies, MDPI, vol. 15(20), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7566-:d:941568
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7566/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/20/7566/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yulin Li & Ben Niu & Guangdeng Zong & Jinfeng Zhao & Xudong Zhao, 2022. "Command filter-based adaptive neural finite-time control for stochastic nonlinear systems with time-varying full-state constraints and asymmetric input saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(1), pages 199-221, January.
    2. Chou, Jui-Sheng & Truong, Dinh-Nhat, 2021. "A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    3. Adam Bondyra & Marek Kołodziejczak & Radosław Kulikowski & Wojciech Giernacki, 2022. "An Acoustic Fault Detection and Isolation System for Multirotor UAV," Energies, MDPI, vol. 15(11), pages 1-19, May.
    4. Yanwei Zhao & Haoyan Zhang & Zhongyu Chen & Huanqing Wang & Xudong Zhao, 2022. "Adaptive neural decentralised control for switched interconnected nonlinear systems with backlash-like hysteresis and output constraints," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(7), pages 1545-1561, May.
    Full references (including those not matched with items on IDEAS)

    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. Liu, Shanlin & Niu, Ben & Zong, Guangdeng & Zhao, Xudong & Xu, Ning, 2022. "Adaptive fixed-time hierarchical sliding mode control for switched under-actuated systems with dead-zone constraints via event-triggered strategy," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    2. Guo, Shiyu & Zhao, Xudong & Wang, Huanqing & Xu, Ning, 2023. "Distributed consensus of heterogeneous switched nonlinear multiagent systems with input quantization and DoS attacks," Applied Mathematics and Computation, Elsevier, vol. 456(C).
    3. Zhao, Yanwei & Wang, Huanqing & Xu, Ning & Zong, Guangdeng & Zhao, Xudong, 2023. "Reinforcement learning-based decentralized fault tolerant control for constrained interconnected nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    4. Ahmed Ginidi & Sherif M. Ghoneim & Abdallah Elsayed & Ragab El-Sehiemy & Abdullah Shaheen & Attia El-Fergany, 2021. "Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    5. Ghareeb Moustafa & Ali M. El-Rifaie & Idris H. Smaili & Ahmed Ginidi & Abdullah M. Shaheen & Ahmed F. Youssef & Mohamed A. Tolba, 2023. "An Enhanced Dwarf Mongoose Optimization Algorithm for Solving Engineering Problems," Mathematics, MDPI, vol. 11(15), pages 1-26, July.
    6. Mohamed Abdel-Basset & Reda Mohamed & Ripon K. Chakrabortty & Michael J. Ryan & Attia El-Fergany, 2021. "An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models," Energies, MDPI, vol. 14(7), pages 1-33, March.
    7. Mahamed G. H. Omran & Maurice Clerc & Fatme Ghaddar & Ahmad Aldabagh & Omar Tawfik, 2022. "Permutation Tests for Metaheuristic Algorithms," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
    8. Mohamed Abdel-Basset & Reda Mohamed & Attia El-Fergany & Sameh S. Askar & Mohamed Abouhawwash, 2021. "Efficient Ranking-Based Whale Optimizer for Parameter Extraction of Three-Diode Photovoltaic Model: Analysis and Validations," Energies, MDPI, vol. 14(13), pages 1-20, June.
    9. Ahmad Taher Azar & Farah Ayad Abdul-Majeed & Hasan Sh. Majdi & Ibrahim A. Hameed & Nashwa Ahmad Kamal & Anwar Jaafar Mohamad Jawad & Ali Hashim Abbas & Wameedh Riyadh Abdul-Adheem & Ibraheem Kasim Ibr, 2022. "Parameterization of a Novel Nonlinear Estimator for Uncertain SISO Systems with Noise Scenario," Mathematics, MDPI, vol. 10(13), pages 1-17, June.
    10. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    11. Hesham Alhumade & Iqbal Ahmed Moujdin & Saad Al-Shahrani, 2023. "Increasing Output Power of a Microfluidic Fuel Cell Using Fuzzy Modeling and Jellyfish Search Optimization," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
    12. Miguel Louro & Luís Ferreira, 2022. "Estimation of Underground MV Network Failure Types by Applying Machine Learning Methods to Indirect Observations," Energies, MDPI, vol. 15(17), pages 1-15, August.
    13. Araby Mahdy & Abdullah Shaheen & Ragab El-Sehiemy & Ahmed Ginidi & Saad F. Al-Gahtani, 2023. "Single- and Multi-Objective Optimization Frameworks of Shape Design of Tubular Linear Synchronous Motor," Energies, MDPI, vol. 16(5), pages 1-27, March.
    14. Liqiong Huang & Yuanyuan Wang & Yuxuan Guo & Gang Hu, 2022. "An Improved Reptile Search Algorithm Based on Lévy Flight and Interactive Crossover Strategy to Engineering Application," Mathematics, MDPI, vol. 10(13), pages 1-39, July.
    15. Ahmed Fathy & Hegazy Rezk & Dalia Yousri & Abdullah G. Alharbi & Sulaiman Alshammari & Yahia B. Hassan, 2023. "Maximizing Bio-Hydrogen Production from an Innovative Microbial Electrolysis Cell Using Artificial Intelligence," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
    16. Abdullah Shaheen & Ragab El-Sehiemy & Salah Kamel & Ali Selim, 2022. "Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm," Energies, MDPI, vol. 15(19), pages 1-14, September.
    17. 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.
    18. Yanhong Feng & Hongmei Wang & Zhaoquan Cai & Mingliang Li & Xi Li, 2023. "Hybrid Learning Moth Search Algorithm for Solving Multidimensional Knapsack Problems," Mathematics, MDPI, vol. 11(8), pages 1-28, April.
    19. Ibrahim Attiya & Laith Abualigah & Samah Alshathri & Doaa Elsadek & Mohamed Abd Elaziz, 2022. "Dynamic Jellyfish Search Algorithm Based on Simulated Annealing and Disruption Operators for Global Optimization with Applications to Cloud Task Scheduling," Mathematics, MDPI, vol. 10(11), pages 1-23, June.
    20. Walaa H. El-Ashmawi & Ahmad Salah & Mahmoud Bekhit & Guoqing Xiao & Khalil Al Ruqeishi & Ahmed Fathalla, 2023. "An Adaptive Jellyfish Search Algorithm for Packing Items with Conflict," Mathematics, MDPI, vol. 11(14), pages 1-28, July.

    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:15:y:2022:i:20:p:7566-:d:941568. 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.