Prediction Method in Improvement of Multi-Hybrid Systems Management (CROSBI ID 588932)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Osman, Krešimir
engleski
Prediction Method in Improvement of Multi-Hybrid Systems Management
The goal of this research is to investigate how few methods can be combined in order to improve management of multi – hybrid systems. Complex analysis of these systems is based on a combination of two approaches: multiple domain matrices (MDM) approach and System Dynamical Behaviour Model approach, which combines few methods and models in order to describe and adjust dynamical behaviour of system, their subsystems and components. These methods and models are: system dynamics, model predictive control, generalized hybrid state model, Liapunov method and Hybrid automata. Prediction method, which is proposed here, model predictive control (MPC) method, is recognized in literature examples, as a very suitable for both, continuous-time and discrete-time prediction, which can be solved in the same framework, multi – dynamic mapping approach, that combined structural and hybrid dynamical system models. With this approach we can better comprehend and manage complexity in multi – hybrid systems. Prediction framework is based to solve engineering problems.
multi-hybrid systems; MDM approach; System Dynamical Behaviour Model approach; system dynamics; model predictive control; generalized hybrid state model; Liapunov method; hybrid automata
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Podaci o prilogu
53-65.
2011.
objavljeno
Podaci o matičnoj publikaciji
2nd TUM Spring School on Systems Engineering - Handout
München:
Podaci o skupu
2nd TUM Spring School on Systems Engineering
predavanje
03.04.2011-06.04.2011
München, Njemačka