2003Unpublished venueRequires access

Fuzzy Modelling and Control of Marine Diesel Engine Prosecc

Radovan Antonić, Zoran Vukić, Ljubomir Kuljača

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Abstract

Marine diesel engine in ship propulsion is very complex and nonlinear plant. In its modelling for diagnosis and control purpose, not only measuring system, but experts knowledge should play important role. The paper gives an introduction of knowledge modelling techniques i.e. fuzzy models suitable for diesel engine diagnosis and control. Two examples are illustrated for engine faulty condition diagnosis and two simulated examples are given for fuzzy control of diesel engine process: 1. diesel oil viscosity control (Mamdani model used) and 2. shaft speed control (T-S model used).

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What this paper is about

Marine diesel engine in ship propulsion is very complex and nonlinear plant. In its modelling for diagnosis and control purpose, not only measuring system, but experts knowledge should play important role. The paper gives an introduction of knowledge modelling techniques i.e. fuzzy models suitable for diesel engine diagnosis and control. Two examples are illustrated for engine faulty condition diagnosis and two simulated examples are given for fuzzy control of diesel engine process: 1. diesel oil viscosity control (Mamdani model used) and 2. shaft speed control (T-S model used).

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Available abstract

Marine diesel engine in ship propulsion is very complex and nonlinear plant. In its modelling for diagnosis and control purpose, not only measuring system, but experts knowledge should play important role. The paper gives an introduction of knowledge modelling techniques i.e. fuzzy models suitable for diesel engine diagnosis and control. Two examples are illustrated for engine faulty condition diagnosis and two simulated examples are given for fuzzy control of diesel engine process: 1. diesel oil viscosity control (Mamdani model used) and 2. shaft speed control (T-S model used).

Key concepts: Diesel engine, Marine propulsion, Diesel fuel, Propulsion, Fuzzy control system, Fuzzy logic, Automotive engineering, Control engineering

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