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This paper describes an enhanced model for the Short Term Hydro Scheduling Problem, HSP, that includes the impact of operation decisions on the market prices and the possibility of adjusting the tailwater level. Additionally, the efficiency of hydraulic turbines is treated as a variable dependent on the discharged flows. The developed solution algorithm uses an iterative approach that solves in each...
The goal of this work is to detect structural damage using vibration-based damage identification approaches even when the damage-sensitive features are camouflaged by the presence of operational and environmental conditions. For feature classification purposes, four machine learning algorithms are applied based on the principal component analysis (PCA), nonlinear PCA, kernel PCA and greedy kernel...
This paper proposes an adaptive approach to improve the performance of Target Controlled Infusion (TCI) based strategies. The method determines an adequate drug dose profile that drives the drug effect on the individual patient to a desired target in a prespecified period of time. It combines an optimal variance constrained drug dose design with a hybrid identification of the individual patient dynamics...
The problem of finding admissible tunings for a PID-controller for automatic neuromuscular blockade drug administration in closed-loop anesthesia is considered. A conventional compartmental pharmacokinetic/pharmacodynamic model with Wiener structure under a PID feedback is analyzed in order to discern the safe intervals of the controller parameters that are free of complex dynamics phenomena. The...
Deep neural networks comprise several hidden layers of units, which can be pre-trained one at a time via an unsupervised greedy approach. A whole network can then be trained (fine-tuned) in a supervised fashion. One possible pre-training strategy is to regard each hidden layer in the network as the input layer of an auto-encoder. Since auto-encoders aim to reconstruct their own input, their training...
In this paper the multiplicative uncertainty in the linearized minimally parameterized parsimonious Wiener model for the neuromuscular blockade is quantified. A set of model parameters was identified from input-output data collected in the surgery room from a population of fifty patients undergoing general anesthesia. The nominal model was considered to be the average of the transfer functions over...
A major obstacle in the design of controllers to regulate the depth of anesthesia (DoA) consists in the high model uncertainty due to inter-patient variability. Surprisingly, the use of control design methods that explicitly tackle this problem is almost absent from the literature on automatic control of anesthesia. In this work, a DoA controller is designed taking into account model uncertainty to...
This paper presents a propagation model for prediction of path loss and performance parameters (throughput and frame loss) on OFDM-based networks. For this study, measurements on a 5.8 GHz Wimax network were carried out. The proposed model parameters have been adjusted by LS (Least Squares) optimization, using measured data as reference. The results show that the proposed model has a good agreement...
Dynamic voltage compensators have been playing important role in the protection of sensitive loads against disturbances, as voltage sags and swells. One implementation option for such equipment is based on the use of a conventional three-phase inverter, which is not able to inject zero sequence components. This paper evaluates the performance of a dynamic sag compensator without zero sequence injection...
During recent years the market for small wind turbine generators (SWTG) has been continuously growing. In this context, the supply of components for this product has also been increasing. The main components of SWTG are the rotor, the generator and the wind energy conversion system (WECS), typically formed by a rectifier plus an inverter. The settings of WECS affect the SWTG behaviour, especially...
In this paper we present a MOSFET-only implementation of a balun LNA. This LNA is based on the combination of a common-gate and a common-source stage with cancelling of the noise of the common-gate stage. In this circuit, we replace resistors by transistors, to reduce area and cost, and minimize the effect of process and supply variations and mismatches. In addition we obtain a higher gain for the...
In this paper, we develop an automated framework for formal verification of timed continuous Petri nets (ContPNs). Specifically, we consider two problems: (1) given an initial set of markings, construct a set of unreachable markings and (2) given a Linear Temporal Logic (LTL) formula over a set of linear predicates in the marking space, construct a set of initial states such that all trajectories...
Combination schemes are gaining attention as an interesting way to improve adaptive filter performance. In this paper we pay attention to a particular convex combination scheme with nonlinear adaptation that has recently been shown to be universal -i.e., to perform at least as the best component filter- in steady-state; however, no theoretical model for the transient has been provided yet. By relying...
This paper presents a methodology for parameter estimation of a nonlinear neuromuscular blockade dynamic model to be used as a predictive model for automated control, in general anesthesia. The neuromuscular blockade dynamic model comprises two blocks connected in series, a pharmacokinetic model and the pharmacodynamic model. The pharmacokinetic model is a second order linear dynamic model and describes...
In this work a new strategy for controlling doubly-fed induction generator is presented. The proposed scheme has two nested control loops. The internal loop regulates the rotor flux, in opposition to the classical approach of controlling the rotor currents. The external loop controls stator currents. Since the machine is connected directly to the grid, this results in a direct control of active and...
In this paper, we develop an automated framework for formal verification of timed continuous Petri nets (contPN). Specifically, we consider two problems: (1) given an initial set of markings, construct a set of unreachable markings, i.e., such that all trajectories starting in the initial set avoid the latter one; (2) given a linear temporal logic (LTL) formula over a set of linear predicates in the...
Fluidification constitutes a relaxation technique to study discrete event systems through a continuous approximated model, thus avoiding the state explosion problem. In this paper, the approximation by Timed Continuous Petri nets under infinite server semantics is studied. The main contribution of this work is the addition of gaussian noise in order to obtain a better (but stochastic) approximation...
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