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About

About

Adjunct professor at Polytechnic Institute of Bragança, Department of Electrotechnics.

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Details

Details

Publications

2020

Performance Enhancement of a Neato XV-11 Laser Scanner Applied to Mobile Robot Localization: A Stochastic Modeling Approach

Authors
Gonçalves, J; Coelho, JP; Braz-César, M; Costa, P;

Publication
Lecture Notes in Electrical Engineering - CONTROLO 2020

Abstract

2020

CDM Controller Design of a Grid Connected Photovoltaic System

Authors
Coelho, JP; Giernacki, W; Gonçalves, J; Boaventura-Cunha, J;

Publication
Lecture Notes in Electrical Engineering - CONTROLO 2020

Abstract

2019

Semi-Active Vibration Control of a Non-Collocated Civil Structure Using Evolutionary-Based BELBIC

Authors
Cesar, MB; Coelho, JP; Goncalves, J;

Publication
Actuators

Abstract
A buildings resilience to seismic activity can be increased by providing ways for the structure to dynamically counteract the effect of the Earth’s crust movements. This ability is fundamental in certain regions of the globe, where earthquakes are more frequent, and can be achieved using different strategies. State-of-the-art anti-seismic buildings have, embedded on their structure, mostly passive actuators such as base isolation, Tuned Mass Dampers (TMD) and viscous dampers that can be used to reduce the effect of seismic or even wind induced vibrations. The main disadvantage of this type of building vibration reduction strategies concerns their inability to adapt their properties in accordance to both the excitation signal or structural behaviour. This adaption capability can be promoted by adding to the building active type actuators operating under a closed-loop. However, these systems are substantially larger than passive type solutions and require a considerable amount of energy that may not be available during a severe earthquake due to power grid failure. An intermediate solution between these two extremes is the introduction of semi-active actuators such as magneto–rheological dampers. The inclusion of magneto–rheological actuators is among one of the most promising semi-active techniques. However, the overall performance of this strategy depends on several aspects such as the actuators number and location within the structure and the vibration sensors network. It can be the case where the installation leads to a non-collocated system which presents additional challenges to control. This paper proposes to tackle the problem of controlling the vibration of a non-collocated three-storey building by means of a brain–emotional controller tuned using an evolutionary algorithm. This controller will be used to adjust the stiffness coefficient of a magneto–rheological actuator such that the building’s frame oscillation under earthquake excitation, is mitigated. The obtained results suggest that, using this control strategy, it is possible to reduce the building vibration to secure levels.

2019

Cyberphysical Network for Crop Monitoring and Fertigation Control

Authors
Coelho, JP; Rosse, HV; Cunha, JB; Pinho, TM;

Publication
Progress in Artificial Intelligence - Lecture Notes in Computer Science

Abstract

2019

Development of a brain emotional learning based controller for application to vibration control of a building structure under seismic excitation

Authors
Braz César, M; Gonçalves, J; Coelho, J; Barros, R;

Publication
COMPDYN Proceedings

Abstract
In this paper, a numerical simulation of a semi-active neuroemotional based control system for vibration reduction of a 3-story framed building structure under seismic excitation is presented. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is used to design a closed-loop control system that determines the required control action (emotional response) based on the desired and actual system response (sensory input). In this case, the control signal is used to adjust in real time the damping force of a MagnetoRheological (MR) damper to reduce the system response. The results obtained from the numerical simulation validate the effectiveness of the brain emotional learning semi-active controller in improving the overall response of the structural system. © 2019 The authors.