Design and Implementation of a Two-Level Supervisory Fuzzy-PID Controller for Microjet Engine

Subject Areas : Mechanical Engineering

Mohsen Shojaei ¹ , Mehdi Jahromi ² , Sayyed Hosseini Sadati ³ , Afshin Valimohammad ⁴

1 - Faculty of Aerospace, Malek Ashtar University of Technology, Iran
2 - Faculty of Aerospace, Malek Ashtar University of Technology
3 - Faculty of Aerospace Engineering, Malek Ashtar University of Technology, Tehran, Iran.
4 - Faculty of Aerospace, Malek Ashtar University of Technology, Iran

Received: 2024-06-06 Accepted : 2024-08-15 Published : 2024-10-06

Keywords: Fuzzy controller, Gas turbine engine, Min-Max control strategy, Two-level controller ,

Abstract :

A detailed modeling of the thermodynamic behavior of the gas turbine engine has been developed in this study. The modeling encompasses volume dynamics, shaft dynamics, Mach number and altitude variation. To achieve maintaining of engine in desired operational range, a two-level hybrid fuzzy-PID controller has been designed for controlling a turbojet engine in a software environment. The effectiveness of this design approach has been investigated, considering all nonlinear thermodynamic behaviors and variations in Mach/altitude. The controller effectively manages these factors and have desire response. Furthermore, a protection loop has been implemented to safeguard against sudden engine shutdown, sharp temperature increases, and surge using the Min-Max strategy coupled with a controller. This approach ensures a safe response of the controller to the engine and prevents damage to the engine. The model possesses the capability to simulate the engine's performance in both transient and steady-state conditions. The validation of the thermodynamic model has been carried out using the GasTurb 13 software to ensure acceptable simulation results. The maximum error was 7% in thrust level. The simulation results indicate the capability of the hybrid two-level controller in various flight scenarios, resulting in an average 18.6% shorter settling time, 34.3% shorter rise time, and no permanent error compared to PID control.

References:

[1] St. Sergui, F. loana, P. Victor and S. Calin, “Gas Turbine Modelling Load Frequency Control”, UP.B. Sci. Bull, Series C, Vol. 70, No. 4, pp. 13-20, (2008).
[2] L.C. Jaw, and J.D. Mattingly, “Aircraft Engine Controls: Design, System Analysis, and Health Monitoring”, American Institute of Aeronautics and Astronautics, Reston, pp. 119-170, (2009).
[3] A. Linke-Diesinger, “Systems of Commercial Turbofan Engines: An Introduction to Systems Functions”, Springer Science & Business Media, Berlin, pp. 85-99, (2008).
[4] S.J. Mohammadi Doulabi Fard, S. Jafari, “Fuzzy Controller Structures Investigation for Future Gas Turbine Aero-Engines”, Int. J. Turbomach. Propuls. Power, Vol. 6, No. 1, pp. 2-24, (2021).
[5] J. Lutambo, J. Wang, Yue, H. Dimirovsky, “G. Aircraft turbine engine control systems development: Historical Perspective”, IEEE, Vol. 34, No. 7260534, pp. 5736-5741, (2015).
[6] K. Michels, F. Klawonn, R. Kruse, A. Nürnberger, “Fuzzy Control”, Springer, Berlin/Heidelberg, pp. 235-256, (2006).
[7] J. F. Silva, S.F. Pinto, “Power Electronics Handbook” , 4th ed., Academic press, San Diego, pp. 1141–1220, (2018).
[8] S.R. Balakrishnan, S.K. Mishra, V. Sundararajan, K.A. Damodaran, “Fuzzy Computing for Control of Aero Gas Turbine Engines”, Def. Sci. J., Vol. 44, No.4, pp. 295–304, (1994).
[9] A.J. Chipperfield, B. Bica, P.J. Fleming, “Fuzzy scheduling control of a gas turbine aero-engine: A multiobjective approach”, IEEE Trans. Ind. Electron, Vol. 49, No. 3, pp. 536–548, (2002).
[10] M. Davoodi, H. Bevrani, "A new application of the hardware in the loop test of the min–max controller for turbofan engine fuel control." Adv. Control Appl.: Eng. and Ind. Syst., Vol. 5, No. 2, pp. 138-154, (2023).
[11] L. Zhimeng, Y. Liu, Youhong Yu, R. Yang, "Advanced fuel limit design to improve dynamic performance of marine three-shaft gas turbine." Appl. Therm. Eng, Vol. 236, No. 1, pp. 121-149, (2024).
[12] N. Hadroug, A. Hafaifa, M. Guemana, A. Kouzou, A. Salam, A. Chaibet, “Heavy duty gas turbine monitoring based on adaptive neuro-fuzzy inference system: Speed and exhaust temperature control”, MICS, Vol. 8, No. 8, pp. 1-20, (2017).
[13] S. Jafari, T. Nikolaidis, “Turbojet engine industrial min-max controller performance improvement using fuzzy norms”, Electronics, Vol. 4, No. 11, pp 314-337, (2018).
[14] H. Guolian, G. Linjuan, H. Congzhi, Z. Jianhua, “ Fuzzy modeling and fast model predictive control of gas turbine system”, Energy, Vol. 200, No. 1, pp. 117-165, (2020).
[15] J. G. Ziegler, N. B. Nichols, “Optimum setting for auto-matic controllers”, Trans. ASME, Vol. 64, No. 8, pp. 759-765, (1942).
[16] A. S. McCormack, K.R. Godfrey, “Rule-based autotuning based on frequency domain identification”, IEEE Trans. Control Syst. Technol., Vol. 6, No. 1, pp. 43–61, (1998).
[17] D. W. Pessen, “A new look at PID-controller tuning”, J. Dyn. Syst. Meas. Control, Vol. 116, No.1, pp. 553–557, (1994).
[18] Z. Y. Zhao, et al, “Fuzzy Gain Scheduling of PID Controllers”, IEEE Trans. Syst. Man Cybern., Vol. 23, No. 5, pp. 1392-1398, (1993).
[19] P. P. Walsh, P. Fletcher, “Gas Turbine Performance”, 2nd ed., Wiley, New York, pp. 61-101, (2004).
[20] A. Kreiner, K. Lietzau, “The Use of Onboard Real-Time Models for Jet Engine Control”, MTU Aero Eng., pp. 1-26, (2002).
[21] H.A. Spang III, H. Brown, “ Control of jet engines”, Control Eng. Pract., Vol. 7, No. 9, pp. 1043-1059, (1999).
[22] I. Moir, A. Seabridge, “Engine Control Systems”, Wiley, New York, pp. 51-86, (2008).