Description du cours

La description du cours est disponible uniquement en croate.

Uvodni sati
Matematički modeli sustava upravljanja u prostoru stanja
Upravljivost i osmotrivost
LQ regulator
Estimator stanja
Adaptivni regulatori
Uvod
Regulatori s podešavanjem pojačanja
Regulatori s unaprijednim signalima (feed forward)
Regulatori s referentnim modelom (MRAS)
Izbor strukture regulatora ? opis procesa
SCADA sustavi upravljanja
Neizrazito upravljanje – Uvod
Projektiranje neizrazitih regulatora
Neizrazito upravljanje – primjeri
Umjetne neuronske mreže
Neuronski regulator

Quand et où

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Acquis d’apprentissage

Les acquis d’apprentissage sont affichés en anglais.

lead projects where involving advance control systems
ability to classify linear and non-linear regulation systems of plants and processes
ability to develop a controller for certain non-linear processes
ability to estimate a suitable adaptive control system for a particular process
ability to integrate a control system based on adaptive, fuzzy control and neuro algorithms

Bibliographie

Bibliographie obligatoire

Z. Vukić, Lj. Kuljača; Automatsko upravljanje – analiza linearnih sustava; Kigen d.o.o.; 2004.
K.J. Astrom; B. Wittenmark; Adaptive Control; Dover Publication; 2008.
D. Đonlagić: Neizraziti regulatori; FER-ZaiPR. 2001.
I. Petrović, M. Baotić, N. Perić; Inteligentni sustavi upravljanja: Neuronske mreže, evolucijski i genetički algoritmi, FER, 2011.

Responsables du cours 2

Intervenants 4

Dates d’examen

dans 10 jours max. dans 30 jours max. plus tard ont eu lieu
Source : ISVU. Un clic sur une session ouvre Studomat pour l'inscription à l'examen ; vérifie-y aussi d'éventuelles modifications.

Systèmes de régulation avancés