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scientific master's theses
Inteligentno upravljanje brodskim procesima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 1999. urn:nbn:hr:168:521521
Velagić, Jasmin
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Control and Computer Engineering

Institutional repository: FER Repository

Cite this document

Velagić, J. (1999). Inteligentno upravljanje brodskim procesima (Scientific master's theses). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:521521

Velagić, Jasmin. "Inteligentno upravljanje brodskim procesima." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 1999. https://urn.nsk.hr/urn:nbn:hr:168:521521

Velagić, Jasmin. "Inteligentno upravljanje brodskim procesima." Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, 1999. https://urn.nsk.hr/urn:nbn:hr:168:521521

Velagić, J. (1999). 'Inteligentno upravljanje brodskim procesima', Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:521521

Velagić J. Inteligentno upravljanje brodskim procesima [Scientific master's theses]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 1999 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:168:521521

J. Velagić, "Inteligentno upravljanje brodskim procesima", Scientific master's theses, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 1999. Available at: https://urn.nsk.hr/urn:nbn:hr:168:521521

Metadata
TitleInteligentno upravljanje brodskim procesima
AuthorJasmin Velagić
MentorZoran Vukić (mentor)
Committee memberLjubomir Kuljača (predsjednik povjerenstva)
Committee memberZoran Vukić (član povjerenstva)
Committee memberVladimir Koroman (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Control and Computer Engineering)
Zagreb
Defense date and country1999-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Cilj ovog rada je primjena inteligentnog upravljanja kod problema vođenja broda po kursu i trajektoriji. Opisani su najčešće korišteni postupci inteligentnog upravljanja i razlozi koji su doveli do njihove izgradnje. Kao autopiloti korišteni su neizraziti (Mamdani, Sugeno) i neuro autopiloti (BP, RB). Opisan je kompletan postupak sinteze neizrazitih autopilota. Neuro autopiloti uči od neizrazitog autopilota, pri čemu se zahtijeva da upravljačke površine neizrazitog i neuro autopilota budu identične (što je moguće bolje). Analiza problema vođenja broda po kursu i trajektoriji sprovedena je na nelinearnim modelima brodova Mariner i ESSO Tanker. Dinamičko ponašanje neizrazitih i neuro autopilota uspoređeno je sa konvencionalnim PID autopilotom. Analiziran je utjecaj valnih poremećaja na dinamičko ponašanje broda pri promjeni kursa i postupci za minimiziranje tog utjecaja. Kod problema vođenja broda po trajektoriji prikazan je manevar zaobilaženja putne točke i vođenje broda po složenoj putanji (trajektoriji). Utjecaj vanjskih hidrodinamičkih poremečaja uslijed mimoilaženja s drugim brodom analiziran je na modelu broda Mariner klase. Efekt plitke vode pri velikom manevru analiziran je na modelu broda ESSO Tanker. Također je razmatran utjecaj morske struje i valova na performanse sustava vođenja broda po trajektoriji. U tu svrhu su projektirani 3-ulazni neizraziti autopiloti (Mamdani, Sugeno), kako bi se poboljšale performanse sustava vođenja. Osim toga, projektiran je i inteligentni autopilot čiju osnovu čine neizraziti autopilot (Mamdani) i mehanizam podešavanja faktora skaliranja. Mehanizam podešavanja predstavlja neizraziti regulator koji mijenja faktore skaliranja osnovnog neizrazitog autopilota.
Abstract (english)
The aim of this paper is intelligent control implementation at course-keeping and track-keeping of ship. The most used intelligent control procedures are described, as well as the reasons that caused their development. Fuzzy logic controllers (Mamdani, Sugeno) and neural networks (Backpropagation, Radial Basis) are used as autopilots. The complete design procedure of fuzzy autopilots is described. Neural autopilot learns from fuzzy autopilot where it is demanded that control surfaces of fuzzy and neural autopilots be identical (as better as possible). Analysis of ship course-keeping and track-keeping problems was performed on the nonlinear ship models Mariner i ESSO Tanker. Dynamical behavior of fuzzy and neural autopilots is compared with conventional PID autopilot. The influence of wave disturbance on dynamical behavior of ship during course-changing and methods for minimizing of that influence are analyzed. On the track-keeping problem the maneuver of way point turning and ship guiding through complex path (trajectory) are presented. The influence of the external hydrodynamic disturbance from passing ship is analyzed on Mariner Class Vessel. The shallow water effect during large maneuver is analyzed on ESSO Tanker. The influence of sea current and wave disturbances on track-keeping performance was also considered. In that purpose 3-input fuzzy autopilots (Mamdani, Sugeno) are designed in order to improve control system performance. Besides, intelligent autopilot is designed and it consists of Mamdani type fuzzy autopilot and mechanism for adjusting of scaling factors. The adjustment mechanism represents fuzzy controller that changes scaling factors of the base fuzzy autopilot.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:521521
Study programmeTitle: Postgraduate master programe in computing
Study programme type: university
Study level: postgraduate
Academic / professional title: magistar inženjer računarstva (magistar inženjer računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2019-03-20 13:21:49