0000000000228223

AUTHOR

Mose' Galluzzo

showing 11 related works from this author

Sviluppo di un sistema di supporto decisionale tipo Fuzzy per il controllo della glicemia post-prandiale nel diabete mellito tipo 1

2010

fuzzy logic system neuro fuzzy system expert system diabetes mellitus glycemia control
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DISPOSITIVO PER RIFLETTERE LA LUCE SOLARE

2016

La presente invenzione si riferisce ad un dispositivo per riflettere la luce solare, e ad un eliostato comprendente tale dispositivo. The present invention relates to a device for reflecting the solar light, and to a heliostat comprising such a device.

Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineSolar energy.
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Adaptive Type-2 Fuzzy Logic Control of Non-Linear Processes

2011

The main objective of this study is to provide a valid and effective approach for the design and development of an adaptive type-2 fuzzy controller (AT2FLC), based on the analysis of the nonlinear process dynamics and the use of an ANFIS technique for the optimization of the controller. The performance of the obtained AT2FLC, characterized by a few number of rules, is higher than the performance of a traditional type-2 fuzzy controller with a larger rule base. The proposed controller is particurarly suitable for the control of processes characterized by uncertainty and time varying parameters.

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimicilcsh:Computer engineering. Computer hardwareComputingMethodologies_DOCUMENTANDTEXTPROCESSINGAdaptive controllcsh:TP155-156Non-linear processeslcsh:TK7885-7895Adaptive control; Type-2 fuzzy control;Non-linear processesType-2 fuzzy controllcsh:Chemical engineeringComputingMilieux_MISCELLANEOUSComputingMethodologies_COMPUTERGRAPHICS
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Integration of HAZOP and FMEA anlyses in an interactive support system

2005

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A design methodology for adaptive type-2 fuzzy controllers

2011

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciType-2 fuzzy controller adapative control
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Development of a predicitive type-2 neurofuzzy controller

2009

A controller that combines the main characteristics and advantages of three different control methodologies is proposed for the control of systems with nonlinearities and uncertainties. A neural network predictive control approach is implemented modifying the output of a controller with a fuzzy logic structure that uses type-2 fuzzy sets. Neural networks are also used to optimize the membership function parameters. The proposed controller is tested by simulation for the control of a bioreactor characterized by bifurcation and parameter uncertainty.

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciPredictive control Type-2 fuzzy logic systems Neurofuzzy control
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Non linear control of glycaemia in type 1 diabetic patients

2011

A fuzzy controller for the closed loop control, by insulin infusion of glycaemia in type 1 diabetic patients is proposed. The controller uses type-2 fuzzy sets. The controller was tested in simulation using a complex nonlinear model of the glucose metabolism. Simulation results confirm the effectiveness and the robustness of the type-2 fuzzy logic controller. The design of the controller uses an optimization method based on genetic algorithms. This makes the type-2 fuzzy controller more efficient and faster than a fuzzy controller with type-1 fuzzy sets, allowing a more accurate control of the glucose in the blood.

Glycemia control; Diabetes; Fuzzy controlSettore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciGlycemia controlFuzzy controlDiabete
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Off-line control of the postprandial glycemia in type 1 diabetes patients by a fuzzy logic decision support

2012

fuzzy logic diabetes
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Neural Network control of a methane oxidation CSTR

2005

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Control of a fermentator for the aerobic growth of saccharomyces cerevisiae by an adaptive type-2 fuzzy logic controller

2008

I controllori a logica fuzzy (FLCs) costituiscono una facile alternativa al controllo di sistemi che hanno un comportamento fortemente non lineare, facendo uso di fuzzy sets e di una logica fuzzy del 1° tipo. A dispetto della loro popolarità però, la ricerca ha mostrato come FLCs di 1° tipo, abbiano difficoltà a gestire e a minimizzare le incertezze presenti in un sistema. Una più grande complessità dei sistemi a logica fuzzy di 2° tipo rispetto quelli del 1° tipo, permette di gestire e conseguentemente di minimizzare gli effetti di una varietà di incertezze che non può essere direttamente gestita da FLS del 1° tipo. In questo lavoro si è considerato l’uso di un FLS del 2° tipo per il contr…

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciFLC adattivo di 2° tipo Biforcazione Stabilità Sistemi non lineari
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A new prototype system for automatic HAZOP analysis

2004

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