Fuzzy modeling of diesel engine based on working position

The paper deals with a problem of nonlinear modeling of diesel engine. A nonlinear fuzzy model based on working position of diesel engine is proposed. The angular velocity of the engine was divided to several segments. For every area, a three-order equivalent linear model was identified with the Correlation Analysis-Least Square method. On the basis of the parameter of linear model, the fuzzy rules were founded. The identification results indicate that the fuzzy modeling method is effective and the nonlinear model is accurate. This nonlinear model can be used to design the control system of diesel engine, and understand its complex dynamics.

[1]  Hong Wang,et al.  Fuzzy modeling via sector nonlinearity concept , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[2]  George W. Irwin,et al.  Robust fuzzy Gustafson–Kessel clustering for nonlinear system identification , 2003, Int. J. Syst. Sci..

[3]  Kazuo Tanaka,et al.  Fuzzy modeling via sector nonlinearity concept , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[4]  Derek A. Linkens,et al.  A systematic neuro-fuzzy modeling framework with application to material property prediction , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[5]  Min-You Chen,et al.  A fast fuzzy modelling approach using clustering neural networks , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[6]  P.K.S. Tam,et al.  A simplified model of fuzzy inference system constructed by using RBF neurons , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[7]  A. Titli,et al.  Neuro-fuzzy modeling of nonlinear systems for control purposes , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[8]  Sei-Wang Chen,et al.  Attributed concept maps: fuzzy integration and fuzzy matching , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Ai Poh Loh,et al.  Modeling pH neutralization processes using fuzzy-neural approaches , 1996, Fuzzy Sets Syst..

[10]  Meng Joo Er,et al.  A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks , 2001, IEEE Trans. Fuzzy Syst..