Functional adaptive uav automatic control system with reference model

Аuthors

Selezneva A. E.

State Research Institute Engineeringpace University, 125, Mira prospect, Moscow, 129226, Russia

e-mail: seleznevaae@yandex.ru

Abstract

This article presents the results of a study on the possibility of using for the object with unknown (not exactly known) dynamic parameters a functional adaptive automatic control system with a reference model based on PID controller. The channel pitch angle of unmanned vehicle moving in different environments is considered as a control object. The principle of operation of a functionally adaptive control system with a reference model is to calculate a controlling influence as the difference between the real states of the control object and the states of the reference model. A mathematical model of a control object with a PID controller was used as a reference model in this article. High accuracy of working out a given effect, even in the case of an inaccurate calculation of the dynamic parameters of the control object, and better resistance to external influences by adjusting the control action in real time are the main advantages of the functional adaptive automatic control system compared to the classic PID controller.

Keywords:

automatic control system; functional adaptive automatic control system; dynamic parameters; reference model; self-adjusting system; PID controller

References

1. Bezyaev V.S., Makarychev P.P. Izvestiya vysshikh uchebnykh zavedenii. Povolzhskii region. Tekhnicheskie nauki, 2020, no. 1 (53), pp. 19–27.
2. Bobtsov A.A., Nikiforov V.O., Pyrkin A.A., Slita O.V., Ushakov A.V. Metody adaptivnogo i robastnogo upravleniya nelineinymi ob"ektami v pribo-rostroenii [Methods of adaptive and robust control of nonlinear objects in instrument engineering], a textbook for higher educational institutions, St. Petersburg, NIU ITMO, 2013. 277 p.  
3. Remen' – Safi. Bol'shaya sovetskaya ehntsiklopediya [The Great Soviet Encyclopedia]. Vol. 22, ed. by А.М. Prokhorov. Moscow, Sovetskaya ehntsiklopediya, 1975, 628 p.
4. Barkana I. Adaptive control? But is so Simple! Journal of Intelligent & Robotic Systems, 2016, no. 83. P. 3–34.
5. Iwai Z., Mizumoto I. Realization of simple adaptive control by using parallel feedforward compensator. International Journal of Control, 1994, vol. 59, iss. 6, pp. 1543–1565.
6. Kaufman H., Barkana I., Sobel K. Direct adaptive control algorithms. N.Y., Springer–Verlag, 1994. xxi, 370 p.
7. Denisenko V.V. Sovremennye tekhnologii avtomatizatsii, 2006, no. 4. pp. 66–74.
8. Selezneva A.E., Neretin E.S. Upravlenie bol'shimi sistemami, 2024, no. 109. pp. 41–66.
9. Lashchev A.Ya. Avtomatika i telemekhanika, 1994, no. 3. pp. 108–116.
10. Ovcharenko V.N. Identifikatsiya aehrodinamicheskikh kharakteristik vozdushnykh sudov po poletnym dannym [Identification of aerodynamic characteristics of aircraft based on flight data], Мoscow, Izd-vo MAI, 2017, 182 p.
11. Adaptive second-order sliding mode conrtol: A Lyapunov approach. IEEE Transactions on Automatic Control, 2022, no. 67 (10), pp. 5392–5399.
12. Wise K.A., Lavretsky E., Hovakimyan N. Adaptive control of flight: theory, applications, and open problems. 2006 American Control Conference IEEE 2006, pp. 5966–5971.
13. Crespo L., Matisutani M., Annaswamy A. Design of a model reference adaptive controller for an unmanned air vehicle. AIAA Guidance, Navigation, and Control Conference, 2010, pp. 8049.
14. Dydek Z.T., Annaswamy A.M., Lavretsky E. Adaptive control of quadrotor UAVs: A design trade study with flight evaluations. IEE Transactions on Control Systems Technology, 2013, vol. 21, iss. 4, pp. 1400–1406.
15. Whitehead B., Bieniawski S. Model reference adaptive control of a quadrotor UAV. AIAA Guidance, Navigation, and Control Conference, 2010, pp. 8148.
16. Shin Y., Calise A. Motter M. Adaptive autopilot designs for an unmanned aerial vehicle. AIAA Guidance, Navigation, and Control Conference and Exhibit, 2005, pp. 6166.
17. Gibson T.E., Annaswamy A, M., Lavretsky E. On adaptive control with closed-loop reference models: transients, oscillations, and peaking. IEE Access, 2013, vol. 1. pp. 703–717.