Comparison of the performance of PID and TVLQR controllers for nonlinear modelling of a freedom flying body

• Autorzy: Fawzy Mohamed , Attar Hani , Amer Ayman , Alsaqoor Sameh , Alahmer Ali , Borowski Gabriel , Solyman Ahmed , As’ad Samer , Agieb Ramy Said

Identyfikatory

DOI

10.15199/48.2024.04.60

Warianty tytułu

PL

Porównanie wydajności kontrolerów PID i TVLQR do modelowania nieliniowego obiektu swobodnie latającego

• Języki publikacji: EN

Abstrakty

EN

The aim of the research was to enhance the trajectory control of a nonlinear freedom flying body model by comparing time-varying linear quadratic regulator (TVLQR) controller with proportional–integral–derivative (PID) control. The nonlinear behavior of the flying body is represented using a linear time-varying (LTV) approach, accounting for parameter variations over time. The equations of motion for the LTV model and the nonlinear flying body were elaborated within the Matlab-Simulink environment. The optimization method was utilized to adapt the PID gains for the simulation of the nonlinear flying body. Their response was then compared to that of identical PID gains implemented on the LTV model. TVLQR optimal controller was generated by solving the Riccati Equation. A comparison between the performance of TVLQR and PID controllers was conducted using a nonlinear flying body. Additionally, the study examined the impact of wind by introducing wind velocity to the velocity of the flying body. In conclusion, we found that the TVLQR controller had better tracking performance, it excelled in actuator deflection, was wind resistant, and effectively dealt with dynamics and actuator uncertainties.

PL

Celem badań było usprawnienie kontroli trajektorii nieliniowego modelu swobodnie latającego obiektu poprzez porównanie regulatora zmiennoprzecinkowego liniowego regulatora kwadratowego (TVLQR) ze sterowaniem proporcjonalno-całkująco-różniczkującym (PID). Nieliniowe zachowanie latającego obiektu przedstawiono za pomocą modelu liniowego zależnego od czasu (LTV), uwzględniającego zmiany parametrów w czasie. Równania ruchu modelu LTV oraz nieliniowego obiektu latającego opracowano w środowisku Matlab-Simulink. Zastosowano metodę optymalizacji w celu dostosowania wzmocnień PID do symulacji nieliniowego obiektu latającego. Ich odpowiedź została następnie porównana z identycznymi wzmocnieniami PID zastosowanymi w modelu LTV. Optymalny kontroler TVLQR został wygenerowany poprzez rozwiązanie równania Riccatiego. Porównanie wydajności regulatorów TVLQR oraz PID przeprowadzono przy użyciu nieliniowego obiektu latającego. W pracy zbadano ponadto wpływ wiatru poprzez wprowadzenie prędkości wiatru do prędkości przemieszczającego się obiektu latającego. W podsumowaniu stwierdzono, że sterownik TVLQR miał lepszą wydajność śledzenia obiektu, wyróżniał się pod względem odchylenia siłownika, był odporny na wiatr i skutecznie poradził sobie z dynamiką i niepewnością siłownika.

Słowa kluczowe

EN

PID controller; TVLQR controller; nonlinear modelling

PL

regulator PID; regulator TVLQR; modelowanie nieliniowe; obiekt swobodnie latający

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 4
• Strony: 291--297
• Opis fizyczny: Bibliogr. 29 poz., rys.

Twórcy

autor

Fawzy Mohamed

• Department of Electrical Engineering, Factly of Engineering, MTI University, Cairo, Egypt

• https://orcid.org/0000-0002-7088-840X

autor

Attar Hani

• Department of Energy Engineering, Zarqa University, Jordan

• https://orcid.org/0000-0001-8028-7918

autor

Amer Ayman

• Department of Energy Engineering, Zarqa University, Jordan

• https://orcid.org/0000-0002-7693-5617

autor

Alsaqoor Sameh

• Applied Science Private University, Amman, Jordan
• Tuskegee University, Tuskegee, AL 36088, United States of America

• https://orcid.org/0000-0002-0552-8926

autor

Alahmer Ali

• Department of Mechanical Engineering, Tafila Technical University, P.O. Box 179, 66110, Tafila, Jordan
• Tuskegee University, Tuskegee, AL 36088, United States of America

• https://orcid.org/0000-0002-2994-1504

autor

Borowski Gabriel

• Faculty of Environmental Engineering, Lublin University of Technology, ul. Nadbystrzycka 40B, 20-618 Lublin, Poland

• https://orcid.org/0000-0001-6971-5395

autor

Solyman Ahmed

• School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow, UK

• https://orcid.org/0000-0002-2881-8635

autor

As’ad Samer

• Renewable Energy Engineering Department, Middle East University, Jordan

• https://orcid.org/0000-0003-4127-3286

autor

Agieb Ramy Said

• School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow, UK

• https://orcid.org/0000-0002-3113-017X

Bibliografia

• [1] Aboelela M.A., Ahmed M.F., Dorrah H.T., Design of aerospace control systems using fractional PID controller. Journal of Advanced Research, 3 (2012), 225–232. https://doi.org/ 10.1016/j.jare.2011.07.003
• [2] Draper C., Guidance is forever. Navigation, 18 (1971), 26–50.
• [3] Spearman M.L., Historical development of worldwide guided missiles: NASA Langley Research Center, 1983.
• [4] Elbes M., Alzubi S., Kanan T., Al-Fuqaha A., Hawashin B. A survey on particle swarm optimization with emphasis on engineering and network applications. Evolutionary Intelligence, 12 (2019), 113–129. https://doi.org/10.1007/s12065-019-00210-z
• [5] Westrum R., Sidewinder: creative missile development at China Lake: Naval Institute Press, 2013.
• [6] Adeli H., Kim H., Wavelet-hybrid feedback-least mean square algorithm for robust control of structures, Journal of Structural Engineering, 130 (2004), 128–137. https://doi.org/10.1061/(ASCE) 0733-9445(2004)130:1(128)
• [7] Agha A., Attar H., Luhach A.K., Optimized economic loading of distribution transformers using minimum energy loss computing. Mathematical Problems in Engineering, (2021), Article ID 8081212. https://doi.org/10.1155/2021/8081212
• [8] Campa G., Algebraic riccati equation solution in simulink via c+ fortran. Matlab Central File Exchange, 2001.
• [9] Zhou K., Doyle J.C., Glover K., Robust and optimal control. Prentice Hall New Jersey, 40 (1996).
• [10] Wu W.-H., Chase J.G., Smith H.A., Inclusion of forcing function effects in optimal structural control. In: Proceedings of the First World Conference on Struct. Control. TP2-22-TP2-31 (1994).
• [11] Ayman A., Hani A., Audih A., Mohammad K.R., Maximizing electrical power saving using capacitors optimal placement. Recent Advances in Electrical & Electronic Engineering; 13 (2020), 7. https://dx.doi.org/10.2174/2352096513666200212103205
• [12] Bigot P., Souza L., Investigation of the state dependent Riccati equation (SDRE) adaptive control advantages for controlling nonlinear systems as a flexible rotatory beam. International Journal of Systems Applications, Engineering and Development., 8, (2014).
• [13] de Souza L.C.G., Design of satellite control system using optimal nonlinear theory. Mechanics Based Design of Structures and Machines, 34 (2006), 351-364. https://doi.org/10.1080/153977306 01044853
• [14] Fawzy M., Aboelela M., El Rhman O.A., Dorrah H., Design of missile control system using model predictive control. Online Journal on Computer Science and Information Technology, 1 (2011), 3, 64–70.
• [15] Abu Qudeiri J.E., Saleh A., Ziout A., Mourad A.-H.I., Abidi M.H., Elkaseer A., Advanced electric discharge machining of stainless steels: Assessment of the state of the art, gaps and future prospect. Materials,12 (2019), 907. https://doi.org/10.3390/ma120 60907
• [16] Siouris G.M., Missile guidance and control systems. Books24x7.com, 2005.
• [17] Ashish T., Modern control design with Matlab and simulink. Indian Institute of Technology, Kanpur, India, John Wiley & Sons (2002).
• [18] Siouris G.M., Missile guidance and control systems. Springer Science & Business Media, 2004.
• [19] Salem N., Study on the effect of vibratory stress relief on the quality of gravity die casting-theory and justifications. In: Proceedings of the 5th International Conference on Advanced Materials, Mechanics and Structural Engineering (5th AMMSE 2018) Seoul, Korea, https://iopscience.iop.org/article/10.1088/1757- 899X/473/1/012041/pdf,
• [20] Stevens B.L., Lewis F.L., Johnson E.N., Aircraft control and simulation: dynamics, controls design, and autonomous systems. John Wiley & Sons, 2015.
• [21] Cook M.V., Flight dynamics principles: A linear systems approach to aircraft stability and control. Butterworth-Heinemann, 2012.
• [22] Salem N., Hussei M.A., Hasan N., Ali A.S., Motion control of ultrasound probe based on master-slave robotic system for medical ultrasound applications. International Journal of Advanced Science and Technology, 28 (2019), 18, 749–759, http://sersc.org/journals/index.php/IJAST/article/view/2793,
• [23] Tyagi A.K., MATLAB and SIMULINK for Engineers: Oxford University Press, 2012.
• [24] MathWorks, MATLAB: the language of technical computing. Desktop tools and development environment, version 7.10.0 vol. 9: MathWorks, 2010.
• [25] Burns R., Advanced control engineering. Butterworth-Heinemann, 2001.
• [26] Tyagi A.K., MATLAB and SIMULINK for Engineers: Oxford University Press, 2012.
• [27] Yuan L., Cui J., Pan M., Liu Y., Design of aerodynamics missile controller based on adaptive fuzzy PID. In: Measurement, Information and Control, International Conference on (2012), 712–716.
• [28] Siouris G.M., Missile guidance and control systems. Springer Science & Business Media, 2004.
• [29] Saadia H., Awan A.U., Khan K.F.A., Liaquat M., Waheed S., Adaptive control of air-to-air missile using multilayer NN feedforward and RISE feedback terms. In: 10th Asian Control Conference, 2015, 1–8.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).