The model based fault detection and identification scheme for the rudder servo system as the actuator in the closed loop course keeping control system is presented. The nonlinear process model that enables description...
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The model based fault detection and identification scheme for the rudder servo system as the actuator in the closed loop course keeping control system is presented. The nonlinear process model that enables description of a wide class of fault types is given and the fault function as the residual for detecting and identifying the fault is introduced. A fault detection scheme with variable thresholds is suggested and its performance has been tested via simulation in the presence of modeling uncertainty and noise. A fault identification scheme based on comparison between the fault function estimate and the output of a predefined analytical fault model is suggested.
The aim of this article is to verify, in the economic feasibility analysis phase, the factors which either promote or limit the successful introduction and implementation of new information technology, and to do this ...
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The aim of this article is to verify, in the economic feasibility analysis phase, the factors which either promote or limit the successful introduction and implementation of new information technology, and to do this by means of a case study. These factors are studied in the framework of the interpretative theory of the evaluation of information technology and the theory of reasoned action in the decision taking process.
作者：
Zoran VukićEdin OmerdićLjubomir KuljacaUniversity of Zagreb
Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia University of Tuzla
Faculty of Electrical and Mechanical Engineering Department of Control Engineering in Automation Franjevačka 2 BH-75000 Tuzla Bosnia and Herzegovina
Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading...
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Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading signal, yaw rate signal and lateral offset from the nominal track to produce a command rudder angle. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. Obtaining of FAM rules for 3-input fuzzy is described. Dynamical behavior of 2 and 3-input fuzzy autopilot is compared. The influence of wave disturbance, sea current and external disturbance from a passing ship on track-keeping performance was analyzed.
Noise reduction, together with signal modelling, classification and prediction, forms a basic problem in many engineering, biomedical and econometric systems. The paper summarizes basic adaptive methods based upon the...
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Noise reduction, together with signal modelling, classification and prediction, forms a basic problem in many engineering, biomedical and econometric systems. The paper summarizes basic adaptive methods based upon the application of artificial neural networks simplified in many cases to an adaptive linear element only. Adaptive noise cancelling algorithms by such finite impulse response (FIR) filters are studied in the first part of the paper both for the case that a reference signal is known and for reference-free structures. Resulting signals are compared with those obtained by noise rejection in the wavelet transform domain either based upon signal decomposition and reconstruction using properly chosen threshold levels for signal modification or incorporating adaptive FIR filtering. Signals preprocessed in this way are then used for their segmentation and classification to verify the effect of signal denoising. Methods presented in the paper are used for simulated signals at first and then applied to the processing of real signals representing physiological signals and technological time series.
Change-point detection is a fundamental problem in many areas of signal segmentation, feature extraction and classification. There are various statistical methods that can be applied to estimate boundaries of signal s...
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Change-point detection is a fundamental problem in many areas of signal segmentation, feature extraction and classification. There are various statistical methods that can be applied to estimate boundaries of signal segments. The paper presents another method based upon the wavelet transform and signal decomposition used to detect signal irregularities. This approach can be very efficient if the initial wavelet function is carefully chosen. Basic methods presented in the paper are verified for simulated sequences at first and then used for biomedical signal segmentation. Resulting algorithms are written in the MATLAB environment.
Based on the research at the location "Middle Adriatic", the analysis of the noise spectrum of the Adriatic Sea is presented. The applied measurement method and necessary instrumentation, followed by the bas...
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Based on the research at the location "Middle Adriatic", the analysis of the noise spectrum of the Adriatic Sea is presented. The applied measurement method and necessary instrumentation, followed by the basic scheme of the measurement channel, are given. A representative Adriatic Sea noise spectrum for the particular location is given, with the sea state as a parameter. A regression analysis is made that led to an appropriate approximation polynomial of the spectrum.
The paper describes the design of a fuzzy logic controller (FLC) to meet required performance specifications in a trajectory following problem involving a laser scanner system. The error and the change of error are us...
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The paper describes the design of a fuzzy logic controller (FLC) to meet required performance specifications in a trajectory following problem involving a laser scanner system. The error and the change of error are used as inputs to the FLC, employing a proportional-derivative structure. A detailed analysis of the design factors is included. The fuzzy logic controller was found to be well suited to the system, yielding results that compared favourably to those obtained by various alternative controllers previously developed for the system.
A method of PID controller autotuning based on relay feedback control is described. Special attention is paid to the process structure and parameters estimation in the phase of reaching the desired operating point. Th...
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A method of PID controller autotuning based on relay feedback control is described. Special attention is paid to the process structure and parameters estimation in the phase of reaching the desired operating point. This may increase the method's robustness and also speed up the tuning procedure. The algorithm's validity is illustrated by some simulation results and an experimental result on a laboratory pilot plant. Il est decrit la mèthode du régulateur d'autoadaptation PID basée au système asservi à relais. L'attention particulierè est consacrée à l'estimation de la structure et des paramètres du procès à la phase dans laquelle on met le proces dans le point de fonetionnement dont on augmente la robustesse et la vitesse de l'autoadaptation. Nous avons presenté certains résultats de la simulation à l'ordinateur ainsi qu'à l'installation pilote qui attestent la validité des algorithmes élaborés.
A fuzzy autopilot for ship path control is proposed. Nonlinear model of a ship and a steering subsystem is used. The autopilot uses heading signal and yaw rate signal to produce a command rudder angle. The autopilot d...
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A fuzzy autopilot for ship path control is proposed. Nonlinear model of a ship and a steering subsystem is used. The autopilot uses heading signal and yaw rate signal to produce a command rudder angle. The autopilot does not use lateral offset from the nominal track. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. The influence of the shallow water effect during larger maneuver is analyzed.
Seasonal time series with dominant frequency components are very common in various information and control systems, biomedicine and environmental engineering. Methods for their analysis, modelling and prediction inclu...
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Seasonal time series with dominant frequency components are very common in various information and control systems, biomedicine and environmental engineering. Methods for their analysis, modelling and prediction include both linear and nonlinear structures using autoregressive models, adaptive systems and neural networks. The paper presents basic algorithms for preprocessing of such signals including their filtering and subsampling at first to enable the following efficient signal approximation, modelling and prediction. The main part of the paper presents the comparison of linear autoregressive models and neural networks with different transfer functions including wavelets as well. Resulting methods presented in the paper are applied for processing of real values representing the river Elbe flow at a selected measuring station to study their modelling and prediction. The paper compares results obtained both by classical and adaptive methods using system history and appropriate learning methods for model optimization.
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