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In nature, an interesting topic is about how a cell can be reconfigured in order to achieve a different task. Another interesting topic is about the learning process that seems to be a trial and error process. In this work, we present mechanisms about how to produce a reconfigurable logical cell based on the tent map. The reconfiguration is realized by modifying its internal parameters generating several logical functions in the same structure. The logical cell is built with three blocks: the initial condition generating function, the tent map, and the output function. Furthermore, we propose a reconfigurable structure based on a chaotic system and an evolutionary algorithm is used in order to tune the parameters of the cell via trial and error process. [ABSTRACT FROM AUTHOR]

Abstract: Distinct robust controllers based on H ∞-theory have been developed to prevent hyperglycemic levels in type I diabetic patients. The underlying idea is that the calculated insulin by these controllers is automatically adjusted by computation and delivered by an insulin pump via intravenous route. Although the evidence shows that severe hyperglycemic condition can be handled by these controllers, none has been tested on possible hypoglycemic scenarios which can be attributable to changes in physiological parameters under action of automatic insulin delivery. In this paper, a computational essay on hypoglycemic scenarios for three robust H ∞ controllers is presented. The objective is to study controllers performance in face to hypoglycemic scenarios induced by metabolic parameters. For this purpose two parameters on hepatic glucose production were selected to test the controllers execution against hypoglycemic scenarios. The results were analyzed statistically resulting similar for the three controllers. Our essay shows conditions such that the analyzed controllers cannot prevent hypoglycemic conditions even if they compute that delivered insulin has to be null at sub-intervals. [Copyright &y& Elsevier]

The operation of anaerobic digestion (AD) has a strong dependence on reliable information about the state variables and kinetic parameters. Such a dependence can lead the AD to restrictions for the implementation of advanced monitoring and automatic control schemes; with consequent implications at operation decisions. An adaptive observer is proposed to advise on organic matter degradation via AD. The underlying idea is to provide a scheme for monitoring simultaneously both the biomass concentration and parameter related to the maximum growth rates. The proposed scheme is based on a dynamical model of two steps wastewater digester which can be written as a general cascade system. The adaptive observer is experimentally evaluated in a pilot-scale anaerobic digester, which is used for the winery wastewater treatment. As a proof-of-principle implementation, the pilot-scale digester is operated under dilution rate with (arbitrary) bounded time-variation. The results show that the proposed estimation approach can provide a reliable information towards the monitoring and full-automation of AD processes. [ABSTRACT FROM AUTHOR]