Application of fuzzy logic algorithms to control the speed of the power turbine of a gas turbine engine

Aircraft engines and power generators


Аuthors

Chicherova E. V.

UEC-Klimov, 11, Kantemirovskaya Str., Saint-Petersburg, 194100, Russia

e-mail: proffgrand@mail.ru

Abstract

The article focuses on the issues of enhancing the quality of electronic system for gas turbine engine automated control. It also analyzes power turbine rotation frequency control loop with various electronic regulators, such as linear PD-controller, PD- controller with reduced the proportional gain, fuzzy P-controller with differential compensating element.

During operation of turbine rotation frequency control loop with initial PD-controller the required transient performance quality can not be provided. Achieving the desired speed of the power turbine is accompanied by an overshoot of about four percent 4% and amplitude ripple of 0.2%. Response time can be up to 20 seconds. Reducing the proportional gain provides aperiodic transient, increases stability margin (no overshoot) and static accuracy. However, required performance cannot be achieved. Transient time comes up to 15 seconds. Fuzzy P-controller provides high static accuracy and performance, but the transient is accompanied by overshoot. To decrease this overshoot and provide aperiodic transition process with fuzzy logic controller differentiator with a negative gain is added. Due to its negative gain, differentiator compensates the overshoot. For controller proper operation differentiator operates in a strictly defined range, when the following error of the power turbine speed falls within the limits of ±[0.25%, 2.9]%.

The developed controller increases the system performance up to 6 seconds, and provides an aperiodic transient, as well as high static accuracy of the system.

The analysis showed that non-linear or piecewise controller is the best choice to ensure the required quality for speed control of a power turbine. For example, it can be PD-controller including a fuzzy P-gain and differentiator with limited interval of operation. Operating range of differentiator depends on power turbine speed mismatch errors.

Keywords:

gas-turbine engine, power turbine, PD controller, fuzzy logic controller

References

  1. Chicherova E.V. Informatsionno-upravlyayushchie sistemy, 2012, no. 6 (61), pp. 33-37.

  2. Egupov N.D. Metody robastnogo, neiro-nechetkogo i adaptivnogo upravleniya (Robust methods, neuro-fuzzy and adaptive control), Moscow, Izd-vo MGTU im. Baumana, 2002, 744 p.

  3. Chicherova E.V. Vestnik Samarskogo gosudarstvennog aerokosmicheskogo universiteta, 2012, no. 3 (34), vol. 1, pp. 145-152.

  4. Grinyaev S. V. Elektronnyi zhurnal «Komp’yuterra», 2001, no. 38, available at: www.computerra.ru (accessed 08.10.2001).

  5. Entsiklopediya ASU TP: Nechetkaya logika, neironnye seti i geneticheskie algoritmy, available at: http://bookasutp.ru/Chapter5_6.aspx

  6. Dudkin Ju.P., Titov Ju.K., Filippenkov R.G., Hizhnjakov Ju.N. Vestnik Moskovskogo aviatsionnogo instituta, 2012, vol. 17, no. 6, pp. 55-60.

  7. Gostev V.I. Nechetkie regulyatory v sistemakh avtomaticheskogo upravleniya (Fuzzy controllers in automatic control systems), Kiev, Radioamator, 2008, 972 p.

  8. Burakov M.V., Konovalov A.S. Informatsionno-upravlyayushchie sistemy, 2011, no. 1 (50), pp. 22-27.

  9. Burakov M.V. Nechetkie regulyatory (Fuzzy controllers), St. Petersburg, Izd-vo GUAP, 2010, 236 p.

  10. Arsen’ev G.N., Shalygin A.A. Informatsionno-izmeritel’nye i upravlyayushchie sistemy, 2011, vol. 9, no. 5. pp. 26-37.

  11. Mallesham G., Rajani A. Automatic tuning of PID controller using fuzzy logic, 8th International Conference on Development and application system, Suceava, Romania, 2006, pp. 120-127.

  12. Ramot D., Friedman M., Langholz, G., Kandel A. Complex fuzzy logic, Fuzzy Systems, IEEE Transactions on, 2003, vol. 11, issue 4, pp. 450-461.


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