Keywords: controller, fuzzy logic, flight dynamics, nonlinearity, uncertainty, model, control, parameter, unmanned aerial vehicle
Adaptive configuration of the fuzzy logic controller of unmanned aerial vehicle flight dynamics
UDC 681.511
DOI: 10.26102/2310-6018/2023.43.4.021
Along with the rapidly growing demand for unmanned aerial vehicles for surveillance and reconnaissance, advanced controllers are needed for these critical systems. This article proposes a design of a flight dynamics controller that takes into account various uncertainties for a medium-range unmanned aerial vehicle. In addition to the nonlinearities of flight dynamics, three main sources of uncertainties caused by unknown controller parameters, simulation errors and external interference are considered. A reliable adaptive fuzzy logic controller responsible for nonlinear flight dynamics under the conditions of many uncertainties has been developed. Nonlinear flight dynamics relies on a soft association of local linear models. When constructing the controller, the optimal reference model is defined, which is stabilized using the linear quadratic controller procedure. Then a fuzzy logic controller is developed for the nonlinear model. In order to eliminate uncertainties, the gain coefficients of the fuzzy logic controller are reconfigured and constantly adjusted for reliable adaptation. The performance of a reliable adaptive fuzzy logic controller is evaluated in terms of stabilizing the transverse and longitudinal flight dynamics and tracking the state variables of the reference model under the conditions of various uncertainties.
1. Verba V.S., Tatarsky B.G. Complexes with unmanned aerial vehicles. Book 1: Principles of construction and features of the use of complexes with unmanned aerial vehicles. Moscow, Radiotekhnika; 2016. 423 p. (In Russ.).
2. Verba V.S. Tatarsky B.G. Complexes with unmanned aerial vehicles. Book 2: Robotic complexes based on unmanned aerial vehicles. Moscow, Radiotekhnika; 2016. 376 p. (In Russ.).
3. Chernodarov A.V. Control, diagnostics and identification of aircraft instruments and measuring and computing complexes. Moscow, Nauchtehlitizdat; 2017. 300 p. (In Russ.).
4. Obolensky Yu.G. Flight control of maneuverable aircraft. Moscow, Voenizdat; 2007. 480 p. (In Russ.).
5. Volobuev M.F. Methods of logical redundancy of control systems of complex technical objects: theory and practice. Voronezh, VUNTS VVS “VVA”; 2017. 294 p. (In Russ.).
6. Radio-electronic equipment and UAV control system. Textbook. Moscow, National Research University “Higher School of Economics”; 2023. 196 p. (In Russ.).
7. Shishkin V.Yu. Volobuev M.F., Skogorev K.K. Detection of gradual failure in a duplicated system using fuzzy logic. Radiotekhnika = Radioengineering. 2017;(11):72–77. (In Russ.).
8. Lysenko L.N., Sham Nguyen Chong. Analysis of the applicability of existing computer technologies for automating the synthesis of fuzzy motion control of a light remotely piloted aircraft in difficult meteorological conditions. Nauchnyi Vestnik MGTU GA = Civil Aviation High Technologies. 2014;(200):118–125. (In Russ.).
9. Ulyanov G.N., Ivanov S.A., Vladyko A.G. The model of controlling the unmanned aerial vehicle with a fuzzy logic controller. Informatsionno-upravliaiushchie sistemy = Information and control systems. 2012;59(4):70–73. (In Russ.).
10. Matveev E.V., Glinchikov V.A. Fuzzy logical inference in the control system of an unmanned aerial vehicle. Zhurnal Sibirskogo federalnogo universiteta. Tekhnika i tehnologii = Journal of Siberian Federal University. Engineering & Technologies. 2011;4(1):79–91. (In Russ.).
11. Karpovich D.S., Shumsky A.N., Saroka V.V. Control system of an unmanned aerial vehicle using the theory of fuzzy sets. Trudy BGTU. Seriia 3: Fiziko-matematicheskie nauki i informatika = Proceeedings of BSTU. Issue 3, physics and mathematics. Informatics. 2016;188(6):110–116. (In Russ.).
12. Caughey D.A. Introduction to aircraft stability and control. Ithaca, New York, Sibley School of Mechanical and Aerospace Engineering. Cornell University; 2011. 153 p.
Keywords: controller, fuzzy logic, flight dynamics, nonlinearity, uncertainty, model, control, parameter, unmanned aerial vehicle
For citation: Potudinskiy A.V. Adaptive configuration of the fuzzy logic controller of unmanned aerial vehicle flight dynamics. Modeling, Optimization and Information Technology. 2023;11(4). URL: https://moitvivt.ru/ru/journal/pdf?id=1466 DOI: 10.26102/2310-6018/2023.43.4.021 (In Russ).
Received 25.10.2023
Revised 22.11.2023
Accepted 13.12.2023
Published 31.12.2023