Title: An adaptive neuro-fuzzy inference system for engineering-vehicle shift decisions

Authors: Wang Zhuo, Zhao Dingxuan

Addresses: Mechanical Electronics Speciality, The College of Mechanical Science and Engineering, JiLin University,The People Street No.142, JiLin, ChangChun, 130025, P.R. China. Mechanical Electronics Speciality, The College of Mechanical Science and Engineering, JiLin University,The People Street No.142, JiLin, ChangChun, 130025, P.R. China

Abstract: To improve the intelligence of engineering vehicle shift decisions, a kind of adaptive neuro-fuzzy inference system (ANFIS) is proposed. A test simulation based on the data that are obtained from a shift experiment on a ZL50E loader transmission system, is also developed. The simulation results show that this shift-decision system can make correct gearbox shift decisions according to the operational situation. This system is an effective method for making shift decisions. It overcomes the shortcoming of fuzzy inference, which doesn|t have a learning function, and the weakness of neural networks which cannot express fuzzy language.

Keywords: ANFIS; engineering vehicle; shift decision.

DOI: 10.1504/IJHVS.2002.001184

International Journal of Heavy Vehicle Systems, 2002 Vol.9 No.4, pp.354-365

Published online: 13 Dec 2003 *

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