Detalhes
Nome
Paulo Moura OliveiraCargo
Investigador SéniorDesde
01 junho 2012
Nacionalidade
PortugalCentro
Centro de Robótica Industrial e Sistemas InteligentesContactos
+351220413317
paulo.moura.oliveira@inesctec.pt
2025
Autores
Tinoco, V; Silva, MF; Santos, FN; Morais, R; Magalhaes, SA; Oliveira, PM;
Publicação
INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL
Abstract
With the global population on the rise and a declining agricultural labor force, the realm of robotics research in agriculture, such as robotic manipulators, has assumed heightened significance. This article undertakes a comprehensive exploration of the latest advancements in controllers tailored for robotic manipulators. The investigation encompasses an examination of six distinct controller paradigms, complemented by the presentation of three exemplars for each category. These paradigms encompass: (i) adaptive control, (ii) sliding mode control, (iii) model predictive control, (iv) robust control, (v) fuzzy logic control and (vi) neural network control. The article further introduces and presents comparative tables for each controller category. These controllers excel in tracking trajectories and efficiently reaching reference points with rapid convergence. The key point of divergence among these controllers resides in their inherent complexity.
2025
Autores
Vrancic, D; Bisták, P; Huba, M; Oliveira, PM;
Publicação
MATHEMATICS
Abstract
The paper presents a new control concept based on the process moment instead of the process states or the process output signal. The control scheme is based on separate control of reference tracking and disturbance rejection. The tracking control is achieved by additionally feeding the input of the process model by the scaled output signal of the process model. The advantage of such feedback is that the final state of the process output can be analytically calculated and used for control instead of the actual process output value. The disturbance rejection, including model imperfections, is controlled by feeding back the filtered difference between the process output and the model output to the process input. The performance of tracking and disturbance rejection is simply controlled by two user-defined gains. Several examples have shown that the new control method provides very good and stable tracking and disturbance rejection performance.
2025
Autores
Benhanifia, A; Cheikh, ZB; Oliveira, PM; Valente, A; Lima, J;
Publicação
Intelligent Systems with Applications
Abstract
Predictive maintenance (PDM) is emerging as a strong transformative tool within Industry 4.0, enabling significant improvements in the sustainability and efficiency of manufacturing processes. This in-depth literature review, which follows the PRISMA 2020 framework, examines how PDM is being implemented in several areas of the manufacturing industry, focusing on how it is taking advantage of technological advances such as artificial intelligence (AI) and the Internet of Things (IoT). The presented in-depth evaluation of the technological principles, implementation methods, economic consequences, and operational improvements based on academic and industrial sources and new innovations is performed. According to the studies, integrating CDM can significantly increase machine uptime and reliability while reducing maintenance costs. In addition, the transition to PDM systems that use real-time data to predict faults and plan maintenance more accurately holds out promising prospects. However, there are still gaps in the overall methodologies for measuring the return on investment of PDM implementations, suggesting an essential research direction. © 2025
2025
Autores
Horst Orsolits; Katrin Clauss; P. B. de Moura Oliveira;
Publicação
Computer Aided Systems Theory – EUROCAST 2024
Abstract
2024
Autores
Schneider, S; Parada, E; Sengl, D; Baptista, J; Oliveira, PM;
Publicação
FRONTIERS IN SUSTAINABLE CITIES
Abstract
Despite the ubiquitous term climate neutral cities, there is a distinct lack of quantifiable and meaningful municipal decarbonization goals in terms of the targeted energy balance and composition that collectively connect to national scenarios. In this paper we present a simple but useful allocation approach to derive municipal targets for energy demand reduction and renewable expansion based on national energy transition strategies in combination with local potential estimators. The allocation uses local and regional potential estimates for demand reduction and the expansion of renewables and differentiates resulting municipal needs of action accordingly. The resulting targets are visualized and opened as a decision support system (DSS) on a web-platform to facilitate the discussion on effort sharing and potential realization in the decarbonization of society. With the proposed framework, different national scenarios, and their implications for municipal needs for action can be compared and their implications made explicit.
Teses supervisionadas
2023
Autor
Hugo Filipe Gonçalves Machado
Instituição
UTAD
2023
Autor
Sílvia de Castro Pereira
Instituição
UTAD
2022
Autor
Milene Sofia Alves Fraga
Instituição
UTAD
2022
Autor
Inês de Almeida
Instituição
UTAD
2021
Autor
Daniel da Silva Duarte
Instituição
UTAD
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