Fuzzy modeling of diesel engine using modified self-organizing map network

Authors:
Jian Zhang;Jingli Kang;Minnan Wang
Affiliations:
School of Mechano-Electronics Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing, 100081, P.R. China;School of Mechano-Electronics Engineering, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing, 100081, P.R. China;Beijing Diesel Locomotive Depot, Beijing, 100022, P.R. China
Venue:
Systems Analysis Modelling Simulation
Year:
2003

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Abstract

This article deals with a problem of nonlinear identification of big power diesel engine 12V1802J equipped on locomotive. A new nonlinear fuzzy model is proposed. The model is identified as black-box model with input-output training data. A modified self-organizing map (MSOM) network is developed for generating parameters of fuzzy model. Based on the MSOM, fuzzy rules are determined automatically according to the distribution of training data in the input-output space and the given approximating error. Simulating result indicates that the nonlinear model depicts the statics and dynamics of diesel engine accurately. This nonlinear model can be used to design the control system of diesel engine, and understand its complex dynamics.