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About

About

Computer engineer with post-doctoral experience in Electrical Engineering at University of Trás-os-Montes and Alto Douro (UTAD, Portugal, 2013) and PhD degree in Automation and Systems from Federal University of Rio Grande do Norte (UFRN), Brazil, in 2007. Professor of Computing/Automation in Brazil (UFRN) since 2003, where has a 13-year experience coordinating academic courses and human resources. Besides, he leaders the electronics laboratory and the research group on Modelling, Instrumentation and Control of Agricultural Systems, where he coordinated/participated in several research projects on technologies of computing and automation applied to agricultural sciences (control systems, embedded systems, digital image processing). Presently, he is a senior researcher at INESC TEC, Portugal. Member of the Brazilian Society of Automation (SBA) and member of the technical commitee of International Federation of Automatic Control (IFAC) on Modelling and Control of Environmental Systems, and Control in Agriculture. Currently is the scientific leader of the ERANET Water JPI project AgriSensus.

Interest
Topics
Details

Details

  • Name

    Josenalde Barbosa Oliveira
  • Cluster

    Industry and Innovation
  • Role

    External Research Collaborator
  • Since

    01st January 2016
Publications

2018

PID Posicast Control for Uncertain Oscillatory Systems: A Practical Experiment

Authors
Oliveira, J; Oliveira, PM; Pinho, TM; Cunha, JB;

Publication
IFAC-PapersOnLine

Abstract

2018

A Sliding Mode-Based Predictive Strategy for Irrigation Canal Pools

Authors
Oliveira, J; Pinho, TM; Coelho, J; Boaventura-Cunha, J; Moura Oliveira, P;

Publication

Abstract
This paper evaluates a robust Model Predictive Controller (MPC) based on Sliding Modes (SMPC) for the downstream level control in irrigation canal pools. Its features are compared with the conventional Generalized Predictive Controller (GPC), regarding set point tracking (water level) and output disturbances (offtake discharges). Simulation results suggest feasibility of applying SMPC for gate manipulation, with suitable command signals and robustness.

2017

Automation and control in greenhouses: State-of-the-art and future trends

Authors
Oliveira, J; Boaventura Cunha, J; Oliveira, PM;

Publication
Lecture Notes in Electrical Engineering

Abstract
This paper presents the state-of-the-art in terms of automation and control for protected cultivation in greenhouses. Aspects such as modeling, instrumentation, energy optimization and applied robotics are considered, aiming at not only to identify latest research topics, but also to foster continuous improvement in key cutting-edge problems. © Springer International Publishing Switzerland 2017.

2017

Comparative Analysis between LDR and HDR Images for Automatic Fruit Recognition and Counting

Authors
Pinho, TM; Coelho, JP; Oliveira, JB; Cunha, JB;

Publication
Journal of Sensors

Abstract
Precision agriculture is gaining an increasing interest in the current farming paradigm. This new production concept relies on the use of information technology (IT) to provide a control and supervising structure that can lead to better management policies. In this framework, imaging techniques that provide visual information over the farming area play an important role in production status monitoring. As such, accurate representation of the gathered production images is a major concern, especially if those images are used in detection and classification tasks. Real scenes, observed in natural environment, present high dynamic ranges that cannot be represented by the common LDR (Low Dynamic Range) devices. However, this issue can be handled by High Dynamic Range (HDR) images since they have the ability to store luminance information similarly to the human visual system. In order to prove their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was carried out. The obtained results show that the use of HDR images improves the detection performance to more than 30% when compared to LDR.

2017

Disturbance rejection improvement for the sliding mode smith predictor based on bio-inspired tuning

Authors
Oliveira, J; Boaventura Cunha, J; Oliveira, PM;

Publication
Lecture Notes in Electrical Engineering

Abstract
This paper addresses a strategy to improve disturbance rejection for the Sliding Mode Controller designed in a Smith Predictor scheme (SMC-SP), with its parameters tuned through the bio-inspired search algorithm—Particle Swarm Optimization (PSO). Conventional SMC-SP is commonly based on tuning equations derived from step response identification, when First Order Plus Dead Time models (FOPDT) are considered and therefore controller parameters are previously set. Online PSO tuning based on minimization of the Integral of Time Absolute Error (ITAE) can provide faster recovery from external disturbances without significant increase of energy consumption, and the Sliding Mode feature deals with possible model mismatch. Simulation results for time delayed systems corroborating these benefits are presented. © Springer International Publishing Switzerland 2017.