A Fuzzy Logic Controller Application for Marine Power Plant


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In order to ensure the quality of marine gas turbine generation set, its speed must maintain constant. Due to rising or falling power demand, the real and reactive power balance is harmed and hence the turbine output speed gets deviated from nominal value. This necessitates the need for an intelligent fuzzy controller to generate and deliver power in an interconnected system as economically and reliably as possible while maintaining the power turbine speed within permissible limits. The design of complex parameter self-tuning fuzzy control system and efficient simulation were achieved. The models were simulated for different load conditions in order to demonstrate the effectiveness of the proposed controller. Simulation results emphasized the improved performance in comparison with fixed gain controllers. The proposed method overcomes the drawbacks of a conventional fixed gain controller and improvement was achieved in terms of settling time, oscillations and overshoot.



Edited by:

Junpeng Shao and Xianli Liu




Z. T. Wang et al., "A Fuzzy Logic Controller Application for Marine Power Plant", Applied Mechanics and Materials, Vol. 274, pp. 616-619, 2013

Online since:

January 2013




[1] Howse M, August/September 2003, All Electric Aircraft, IEE Power Engineer, pp.35-37.

[2] McCallum Lt N R, Green A and Mason S C, 2004, Electric Start Systems for Gas Turbines – A Means to Self Sustainability, Proc PAC 2004, 3-5th Feb 2004, Sydney, Australia.

[3] Chen Guojun, ZengFanming.Modern Ships Turbine Project[M].Changsha:Defense Science and Technology University Press,2001:2-15.

[4] Qin lixin,Chachangsong,Xujianzhong.The Vessel Integrated Electric Propulsion System Development and Application[J].Marine Science and Technology,2009,31(5):42-45.

[5] A. Soundarrajan and S. Sumathi. Fuzzy-based intelligent controller for power generating systems[J] Vibration and Control, 2011, 17(8) 1265–1278.

DOI: https://doi.org/10.1177/1077546310371347

[6] Mathur HD and Manjunath HV (2007) Frequency stabilization using fuzzy logic based controller for multi-areapower system. South Pacific Journal of Natural Science4: 22–30.

DOI: https://doi.org/10.1071/sp07004

[7] M. Santos, A.L. Dexter, Control of a cryogenic process using a fuzzy PID scheduler, Contr. Eng. Practice 10 (10) (2002) 1147–1152.

DOI: https://doi.org/10.1016/s0967-0661(02)00062-x

[8] K.K. Ahn, D.Q. Truong, Online tuning fuzzy PID controller using robust extendedKalman filter, J. Process Contr. 19 (6) (2009) 1011–1023.

DOI: https://doi.org/10.1016/j.jprocont.2009.01.005

[9] W.D. Chang, R.C. Hwang, J.G. Hsieh, A self-tuning PID control for a class of nonlinearsystems based on the Lyapunov approach, J. Process Contr. 12 (2) (2002)233–242.

[10] Y. Kansha, L. Jia, M.S. Chiu, Self-tuning PID controllers based on the Lyapunovapproach, Chem. Eng. Sci. 63 (10) (2008) 2732–2740.

DOI: https://doi.org/10.1016/j.ces.2008.02.026