Abstract System identification as a field has been around since the 1950s with roots from statistical theory. A substantial body of concepts, theory, algorithms and experience developed then. Indeed, there is very extensive literature on subject, many text books, like [5, 8, 12]. Some main points this “classical” are summarized in chapter, just pointing to basic structure problem area. The cent...

Swarm-based metaheuristics have shown significant progress in solving different complex optimization problems, including the parameter identification of linear, as well nonlinear, systems. Nonlinear systems are inherently stiff and difficult to optimize and, thus, require special attention effectively estimate their parameters. This study investigates an input nonlinear autoregressive exogenous...

BACKGROUND The technological advancements in subcutaneous continuous glucose monitoring and insulin pump delivery systems have paved the way to clinical testing of artificial pancreas devices. The experience derived by clinical trials poses technological challenges to the automatic control expert, the most notable being the large interpatient and intrapatient variability and the inherent uncert...

Ex-vivo expansion of adult human islet β cells has been evaluated for generation of abundant insulin-producing cells for transplantation; however, lineage-tracing has demonstrated that this process results in β-cell dedifferentiation. Redifferentiation of β-cell-derived (BCD) cells can be achieved using a combination of soluble factors termed Redifferentiation Cocktail (RC); however, this treat...

Abstract Improving the geometric accuracy of deposited component is essential for wider adoption wire arc additive manufacturing (WAAM) in industries. This paper introduces an online layer-by-layer controller that operates robustly under various welding conditions to improve deposition WAAM process. Two control strategies are proposed and evaluated this work: A PID algorithm a multi-input multi...

In this paper we assess how intra-day electricity prices can improve the prediction of zonal day-ahead wholesale in Italy. We consider linear autoregressive models with exogenous variables (ARX) and without interactions among predictors, non-parametric taken from machine learning literature. particular, implement Random Forests support vector machines, which should automatically capture relevan...