Guilherme Ramos; A. PedroAguiar; Sérgio Pequito Automatica DOI: https://doi.org/10.1016/j.automatica.2022.110229 Abstract(EN): This paper provides an overview of the research conducted in the context of structural (or structured) systems. These are parametrized models used to assess and design system theoretical properties without considering a specific realization of the parameters (which could be uncertain or unknown). The research […]
Model Predictive Control for Self Driving Cars: A Case Study Using the Simulator CARLA within a ROS Framework
Daniel R Morais, A Pedro Aguiar ICARSC 2022 DOI: 10.1109/ICARSC55462.2022.9784788 Abstract(EN): Over the past few years, autonomous driving vehicles have been growing rapidly due to advances in technology, namely computing power and improvements in sensors and actuators. This paper presents a research work that addresses the autonomous driving problem. More specifically, a Model Predictive Control […]
A Path-Following Controller for Marine Vehicles Using a Two-Scale Inner-Outer Loop Approach
Pramod Maurya, Helio Mitio Morishita, Antonio Pascoal, A. Pedro Aguiar Sensors (MDPI) DOI: 10.3390/s22114293 Abstract(EN): This article addresses the problem of path following of marine vehicles along straight lines in the presence of currents by resorting to an inner-outer control loop strategy, with due account for the presence of currents. The inner-outer loop control structures exhibit […]
A Secure Federated Deep Learning-Based Approach for Heating Load Demand Forecasting in Building Environment
Moradzadeh, A.; Moayyed, H.; Mohammadi Ivatloo, B.; Aguiar, AP. ; Anvari Moghaddam, A. IEEE Acces ID Authenticus: P-00V-ZNM DOI: 10.1109/access.2021.3139529 Abstract (EN): Recently, with the establishment of new thermal regulations, the energy efficiency of buildings has increased significantly, and various deep learning-based methods have been presented to accurately forecast the heating load demand of buildings. However, all of […]