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D2.4 Report on the developed approach to systematic uncertainty handling in economics- driven coordination for SoS control (CROSBI ID 778721)

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Đalto, Mladen ; Novoselnik, Branimir ; Baotić, Mato ; Vašak, Mario ; Matuško, Jadranko ; Jokić, Andrej. D2.4 Report on the developed approach to systematic uncertainty handling in economics- driven coordination for SoS control // DYMASOS deliverable 2.4. 2016.

Podaci o odgovornosti

Đalto, Mladen ; Novoselnik, Branimir ; Baotić, Mato ; Vašak, Mario ; Matuško, Jadranko ; Jokić, Andrej.

engleski

D2.4 Report on the developed approach to systematic uncertainty handling in economics- driven coordination for SoS control

In this deliverable we describe the work carried out within the Work Package 2, Task 2.4, where the main objective is development of computationally tractable robust and stochastic methodology for the coordination and management of systems of systems that takes into account the uncertainty and disturbances at system level. First we present an extension of our approach for the optimal coordination of systems of systems based on parametric optimization that was outlined in D2.2. Particularly, in D2.2 we used a rather limiting assumption of a single coupling constraint to show that the on-line coordination of systems of systems can be computed with a very efficient linear-time algorithm. Here, we show that a linear-time algorithm for the coordination of systems of systems can be constructed in a more general setting of multiple coupling constraints as well. Furthermore, we illustrate how uncertainties and disturbances can be taken into account within our approach, both in robust and stochastic fashion. In addition to literature review of different methods for uncertainty handling within the general framework of model predictive control, we also present two methods based on a tube scaling approach for robust and stochastic control of systems of systems. Throughout the report we use examples stemming from the HEP case study to verify the proposed methods.

robust control ; stochastic control ; multi-parametric programming ; optimal coordination ; model predictive control ; systems of systems

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Podaci o izdanju

DYMASOS deliverable 2.4

2016.

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objavljeno

Povezanost rada

Elektrotehnika, Temeljne tehničke znanosti

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