Radovan Antonić

Analytical Determination of Describing Function of Nonlinear Element with Fuzzy Logic

The paper presents the procedure for analytical determination of describing function of nonlinear element with fuzzy logic nonlinearity. The procedure is based on the method of analytical determination of describing function of generalized static characteristic of nonlinear element. The procedure is also illustrated with examples.

Improved line-of-sight guidance for cruising underwater vehicles

Abstract Guidance through waypoints is common for small autonomous marine vehicles. Guidance by the line of sight, which turns the vehicle directly towards the next waypoint without any reference path calculation, is computationally the simplest form of waypoint guidance. However, the basic algorithm gives rather poor guidance due to the missed waypoint problem, lack of sea current compensation and abrupt transitions between the consecutive waypoints. Significant path deviations and even deadlocks are possible due to these problems. Therefore, more complex algorithms are usually used in real world applications. The research reported in this paper aims to demonstrate that significant improvements of the basic line-of-sight guidance algorithm can be achieved by several intuitive, simple corrections and additions. The simplicity of the basic line-of-sight guidance algorithm is not compromised. In particular, missed waypoint detection is performed by monitoring the distance between the vehicle and the waypoint. Introduced reference heading corrections are based upon the location of the next waypoint after the one the vehicle is currently approaching, and upon the sea current direction and intensity. The results of these corrections are shown in several simulation examples. In addition, the paper includes a short discussion about the line-of-sight guidance in the diving plane.

Marine Diesel Engine Process Modelling and Control Using Advanced Technologies

The paper presents some possibilities of practical use of advanced computing technologies applied to the modelling and control of marine diesel engine. The emphasis is put on two well recognised techniques, fuzzy logic and artificial neural networks. Because of the complexity of diesel propulsion engine working in changeable operating regimes and environmental conditions at sea, it is highly desirable to have adaptive control system capable of accommodating to such situations. We propose here an effective method of engine control system design using multiple engine models and adequate algorithms with learning and adapting possibilities to different operating and environmental conditions. Simulation examples applied to marine diesel engine of MAN B&W 6L60MC type show advantages of using combined methods and techniques in engine modelling and control.

Neuro-fuzzy modelling of marine diesel engine cylinder dynamics

Abstract In this paper, the practical application of some well recognised fuzzy methods and neural networks techniques to modelling marine diesel engine cylinder dynamics using real-time data and expert knowledge has been considered. The simulation was done in Matlab environment with real-time data originated from 2-stroke marine diesel propulsion engine on test bed during final testing, combined with knowledge elicited from engine experts and experienced test bed operators. Takagi-Sugeno fuzzy model has been designed based on cylinder pressure data after their clustering using fuzzy subtractive method. Model parameter tuning was investigated using ANFIS with combined learning algorithms: least-squares and back-propagation gradient descent method. The model obtained can be of practical importance in engine working regime adjustment, predicting cylinder data in faulty sensor case or adaptive threshold tuning within faults detection and identification.

Marine Diesel Engine Faults Diagnosis Based on Observed Symptoms and Expert Knowledge

Abstract The paper deals with two methods to fault detection and isolation in ships propulsion diesel engine. The first diagnosis method is based on real-time diagnostic signals i.e. symptoms and their relation to faults in an extended form with tracking times of symptoms occurrence. The effectiveness of this method has been evaluated with concurrently simulating two very similar engine cylinder faults. The second diagnosis method introduced in the paper based on human expert heuristic knowledge showed very good result in diagnosis the same engine fault. In both simulation examples, in a certain way, a form of integration of these two methods is used. The hybrid method based on good monitoring system and heuristic knowledge base could become more attractive in marine applications.