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New times demand new teaching and learning methodologies. A partial flipped classroom methodology was tested in a modelling and feedback control course for undergraduate biomedical engineering. A semester course was divided in two parts: the first half using a flipped approach and the second one using a classical approach. The experience results are reported, presenting the methodology ups and downs...
Multidimensional systems, or n-D systems, are systems having several independent variables. Several topics, in particular stability, of n-D systems (n > 1) have attracted the interest of many researchers. The main reason, is because the extension stability theory of 1-D systems to systems with higher dimensions is not straightforward. In this paper, two adopted meta-heuristics algorithms are used...
This paper presents a Quantum Particle Swarm Optimization (QPSO) applied to hour-ahead scheduling in Smart Grid (SG). The unforeseen events not considered in day-ahead scheduling, must be overcome when approaching intraday operation. This implies new constraints in hour-ahead formulation. The developed methodology aims to complement the day-ahead scheduling tools already available on the literature...
This paper presents an experiment concerning the development of two mobile devices applications with the App Inventor 2 for Android operating systems. These applications are intended to support teaching and learning activities in Industrial Automation and Control courses, particularly concerning logic control, logic controller programming and process control. While the reported applications: eLogicum...
This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case...
Multi-objective optimization inspired on genetic algorithms are population based search methods. The population elements, chromosomes, evolve using inheritance, mutation, selection and crossover mechanisms. The aim of these algorithms is to obtain a representative non-dominated Pareto front from a given problem. Several approaches to study the convergence and performance of algorithm variants have...
A simulation teaching experiment to control a gantry crane system is proposed. The control is performed both in open-loop and closed-loop. The open-loop control is based on the Posicast feedforward technique and the closed-loop control uses a two-degrees of freedom configuration. Posicast control is used as a pre-filter outside the feedback loop to enhance the setpoint tracking response and a PID...
Diffusion of innovation is a research topic which has been subject to several works in the last years. The diffusion of innovation theory aims to explain how new ideas and practices are disseminated between the members of a social system. A significant part of the existing models are based on the use of parameters which determine the process of innovation adoption, and rely on simple mathematical...
This paper presents a genetic algorithm to optimize uni-objective problems with an infinite number of optimal solutions. The algorithm uses the maximin concept and e-dominance to promote diversity over the admissible space. The proposed algorithm is tested with two well-known functions. The practical results of the algorithm are in good agreement with the optimal solutions of these functions. Moreover,...
A genetic algorithm used to design radio‐frequency binary‐weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. The algorithm provides a set of circuits all having the same maximum performance. This article also describes the design, implementation, and measurements results of a 0.25 μm BiCMOS 3‐bit RFDSCA. The experimental results show that the circuit presents the...
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