An ANFIS Solution for Real-Time Control of the EGR & VGT in a Diesel Engine

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Abstract:

An ANFIS (Adaptive neuro-fuzzy inference system) controller which bases on Takagi-Sugenos method and combines the advantages of neural controller and fuzzy multi-variable controller has been studied and developed for the real-time control of EGR and VGT in a diesel engine. In the AVL-BOOST and Matlab/Simulink co-simulation environment, the control performance of ANFIS controller has been compared with those optimal control strategies based on a fuzzy logic controller. Results show the new controller can have more active control to EGR position and the optimal emission levels can be maintained.

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Periodical:

Advanced Materials Research (Volumes 732-733)

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1222-1225

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Online since:

August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Y. -Y. Wang, et al., Quantitative feedback design of air and boost pressure control system for turbocharged diesel engines, Control engineering practice, vol. 19, pp.626-637, (2011).

DOI: 10.1016/j.conengprac.2011.02.006

Google Scholar

[2] J. -F. Arnold, et al., Fuzzy controller of the air system of a diesel engine: Real-time simulation, European journal of operational research, vol. 193, pp.282-288, (2009).

DOI: 10.1016/j.ejor.2007.08.046

Google Scholar

[3] Maiboom, et al., Experimental study of various effects of exhaust gas recirculation (EGR) on combustion and emissions of an automotive direct injection diesel engine, Energy, vol. 33, (2008).

DOI: 10.1016/j.energy.2007.08.010

Google Scholar

[4] R. Omran, et al., Optimal control of a variable geometry turbocharged diesel engine using neural networks: applications on the ETC test cycle, IEEE transactions on control systems technology, (2008).

DOI: 10.1109/tcst.2008.2001049

Google Scholar

[5] J. F. Arnold, et al., Control of the air system of a diesel engine: A fuzzy multivariable approach, presented at the International conference on control applications, Munich, Germany, (2006).

DOI: 10.1109/cca.2006.286196

Google Scholar