Enhancing the Performance of Jet Engine Fuel Controller Using Neural Networks

Abstract:

This paper proposes a fuzzy logic controller for a specific turbojet engine. The turbine engines require control systems to achieve the appropriate performance. The control systems typically featured loops to prevent engine flame out, over speeds, compressor surge, and check turbine inlet temperature limit, either by scheduling the fuel flow during accelerations and decelerations or by controlling the acceleration and deceleration rates of engine spool. This paper presents a successful approach in designing a Fuzzy Logic Controller for a specific Jet Engine. At first a suitable mathematical model for the jet engine is presented by the aid of SIMULINK simulation software. Then by applying different reasonable fuel flow functions via the engine model, some important engine continuous time operation parameters (such as: thrust, compressor surge margin, turbine inlet temperature and engine spool speed...) are obtained. These parameters provide a precious database which can be used by a neural network. At the second step, by designing and training a feedforward multilayer perceptron neural network according to this available database; a number of different reasonable fuel flow functions for various engine acceleration operations are determined. These functions are used to define the desired fuzzy fuel functions. Indeed, the neural networks are used as an effective method to define the optimum fuzzy fuel functions. At the next step we design a fuzzy logic controller by using the engine simulation model and the neural network results. The proposed control scheme is proved by computer simulation using the designed engine model. The simulation results of engine model with fuzzy controller in comparison with the engine testing operation illustrate that the proposed controller achieves the desired performance.

• Periodical: Applied Mechanics and Materials (Volume 390)
• Pages: 393-397
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.390.393
• Online since: August 2013
• Authors: Mehrdad Bazazzadeh, Ali Shahriari
• Keywords: Engine Modeling, Fuzzy Controller, Gas Turbine, Jet Engine, Neural Network (NN)

References

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DOI: 10.2514/6.2009-5525

[2] H. Badihi, A. Shahriyari, Alir. Naghsh, Artificial Neural Network Application to Fuel Flow Function for Demanded Jet Engine Performance, 2009 IEEE/AIAA Aerospace Conference, Big Sky, Montana, USA.

DOI: 10.1109/aero.2009.4839656

[3] Andrew J. Chipperfield, Beatrice Bica, and Peter J. Fleming, Fuzzy Scheduling Control of a Gas Turbine Aero-Engine: A Multiobjective Approach, Journal of IEEE Transactions on Industrial Electronics, Vol. 49, No. 3, JUNE (2002).

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