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Neuro-fuzzy identification of an internal combustion engine

Tuan Kamaruddin, Tengku Nordayana Akma and Mat Darus, Intan Z (2012) Neuro-fuzzy identification of an internal combustion engine. International Journal of Simulation Systems, 13 (3B). pp. 30-37. ISSN 1473-804X E-ISSN 1473-8031

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Dynamic modeling and identification of an internal combustion engine (ICE) model is presented in this paper. Initially, an analytical model of an internal combustion engine simulated within SIMULINK environment is excited by pseudorandom binary sequence (PRBS) input. This random signals input is chosen to excite the dynamic behavior of the system over a large range of frequencies. The input and output data obtained from the simulation of the analytical model is used for the identification of the system. Next, a parametric modeling of the internal combustion engine using recursive least squares (RLS) technique within an auto-regressive external input (ARX) model structure and a nonparametric modeling using neuro-fuzzy modeling (ANFIS) approach are introduced. Both parametric and nonparametric models verified using one-step-ahead (OSA) prediction, mean squares error (MSE) between actual and predicted output and correlation tests. Although both methods are capable to represent the dynamic of the system very well, it is demonstrated that ANFIS gives better prediction results than RLS in terms of mean squares error achieved between the actual and predicted signals.

Item Type: Article (Journal)
Additional Information: 8411/78965
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1 Motor vehicles
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User: Dr Tengku Nordayana Akma Tuan Kamaruddin
Date Deposited: 16 Mar 2020 15:26
Last Modified: 16 Mar 2020 15:27
URI: http://irep.iium.edu.my/id/eprint/78965

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