Darine Zambrano

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The study presents a robust closed-loop sliding mode controller with internal model for blood glucose control in type-1 diabetes. Type-1 diabetic patients depend on external insulin delivery to keep their blood glucose within near-normal ranges. Closed-loop artificial pancreas is developed to help avoid dangerous, potentially life-threatening hypoglycemia,(More)
Patients with type 1 diabetes require insulin therapy to maintain blood glucose levels within safe ranges since their pancreas is unable to complete its function. The development of a closed-loop artificial pancreas capable of maintaining normoglycemia during daily life will dramatically improve the quality of life for insulin-dependent diabetic patients.(More)
This paper deals with the identification of the nitrogen oxide emissions (NOx) from vehicles using the selective catalyst as an aftertreatment system for its reduction. The process is nonlinear, since the chemical reactions involved are highly depending on the operating point. The operating point is defined by the driving profile of the vehicle, which(More)
A design of a novel model predictive controller is presented. The proposed Sliding Mode Predictive Control (SMPC) algorithm combines the design technique of Sliding-Mode Control (SMC) with Model based Predictive Control (MPC). The SMPC showed a considerable robustness improvement with respect to MPC in the presence of time delay, and showed an enhanced(More)
Iterative Learning Controller (ILC) built on top of conventional controls helps the plant to effectively track its reference signals under repetitive conditions. Research devoted to this has been an extensive topic in last decade and so were the practical applications, that cover manufacturing systems, chemical processes, robotics, etc. In this paper we(More)
The zero-temperature, classical XY model on an L×L square lattice is studied by exploring the distribution Φ_{L}(y) of its centered and normalized magnetization y in the large-L limit. An integral representation of the cumulant generating function, known from earlier works, is used for the numerical evaluation of Φ_{L}(y), and the limit distribution(More)
In this paper we propose a method to study critical systems numerically, which combines collective-mode algorithms and renormalization group on the lattice. This method is an improved version of the Monte Carlo renormalization group in the sense that it has all the advantages of cluster algorithms. As an application we considered the 2D Ising model and(More)
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