IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i8p2292-d538987.html
   My bibliography  Save this article

Adaptive Control and Estimation of the Condition of a Small Unmanned Aircraft Using a Kalman Filter

Author

Listed:
  • Dávid Megyesi

    (Department of Avionics, Faculty of Aeronautics, Technical University of Košice, 040 01 Košice, Slovakia)

  • Róbert Bréda

    (Department of Avionics, Faculty of Aeronautics, Technical University of Košice, 040 01 Košice, Slovakia)

  • Martin Schrötter

    (Department of Avionics, Faculty of Aeronautics, Technical University of Košice, 040 01 Košice, Slovakia)

Abstract

The article was motivated by the design of adaptive control algorithms for the control of a a fixed wing unmanned aerial vehicle (UAV). An adaptive system is a system that, with its structure or parameters, adapts to changes in the behavior of the object and based on the knowledge of variable properties, maintains the quality of its regulatory transition. The knowledge gained on this small UAV can be applied to larger aircraft. The creation of the proposed adaptive control into the UAV consisted of the creation of a simulation model of the aircraft based on known physical laws, the properties of the aircraft and a mathematical description. An adaptive PID controller for stabilization with changing coefficients based on the airspeed of the aircraft was designed and simulated. A validated control of the mathematical model of an unmanned aircraft was designed and simulated using the methods of estimation and identification of the UAV model parameter based on measured data from flight tests. Identifying dynamic parameters is a challenging task due to several factors, such as random vibration noise, interference, and sensor measurement uncertainty. The designed adaptive UAV control provides very promising results in improving the controllability of the aircraft while reducing the effect of speed changes on the stability and controllability of the system compared to the conventional PID controller. The comparison was performed on three selected types of PID controllers. The first type had fixed coefficients for the entire range of speeds calculated using the Control toolbox in MatLab. The second type also had constant coefficients over the entire range of speeds calculated using the Naslin method. The third adaptive type of PID controller had variable coefficients based on approximate polynomials dependent on the change in flight speed. The reason for the comparison was to show an increase in margin of stability using the method of variable coefficients of the PID controller based on the change of flight speeds. The obtained results show that the proposed adaptive control algorithm is robust enough to control the movement of the aircraft in the longitudinal plane and due to the introduced process and measurement errors, while the used Kalman filter effectively eliminates these errors.

Suggested Citation

  • Dávid Megyesi & Róbert Bréda & Martin Schrötter, 2021. "Adaptive Control and Estimation of the Condition of a Small Unmanned Aircraft Using a Kalman Filter," Energies, MDPI, vol. 14(8), pages 1-24, April.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2292-:d:538987
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/8/2292/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/8/2292/
    Download Restriction: no
    ---><---

    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:14:y:2021:i:8:p:2292-:d:538987. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.