Autonomous Robotics Vehicles
Publications on Autonomous Robotics Vehicles
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 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…
Energy-Optimal Motion Planning for Multiple Robotic Vehicles With Collision Avoidance
Hausler, AJ; Saccon, A; Aguiar, AP; Hauser, J; Pascoal, AM IEEE Transactions on Control Systems Technology ID Authenticus: P-00R-YR9 DOI: 10.1109/TCST.2015.2475399 Abstract:We propose a numerical algorithm for multiple-vehicle motion planning that explicitly takes into account the vehicle dynamics, temporal and spatial specifications,…
Moving Path Following for Unmanned Aerial Vehicles With Applications to Single and Multiple Target Tracking Problems
Oliveira, T; Aguiar, AP; Encarnacao, P IEEE Transactions on Robotics ID Authenticus: P-00K-VS8 DOI: 10.1109/tro.2016.2593044 Abstract: This paper introduces the moving path following (MPF) problem, in which a vehicle is required to converge to and follow a desired geometric moving path, without a…
Safe Coordinated Maneuvering of Teams of Multirotor Unmanned Aerial Vehicles: A Cooperative Control Framework For Multivehicle, Time-Critical Missions
Cichella, V; Choe, R; Mehdi, SB; Xargay, E; Hovakimyan, N; Dobrokhodov, V; Kaminer, I; Pascoal, AM; Aguiar, AP IEEE CONTROL SYSTEMS MAGAZINE ID Authenticus: P-00K-SAC DOI: 10.1109/mcs.2016.2558443 Abstract: Multirotor unmanned aerial vehicles (UAVs) have experienced a very fast-paced technological development over the past…
Nonlinear Control and Estimation
Publications on Nonlinear Control and Estimation
Sliding Mode Fault-Tolerant Controller for Overactuated Electric Vehicles with Active Steering
Lopes, A; Rui Esteves Araújo; Aguiar, AP; Maria do Rosário de Pinho IECON Proceedings (Industrial Electronics Conference) ID Authenticus: P-00M-CR2 DOI: 10.1109/iecon.2016.7793205 Abstract: This paper addresses the tracking problem of the state variables of a nonlinear planar dynamic model of an overactuated electric…
On the Design of Discrete-Time Economic Model Predictive Controllers
Alessandretti, A; Aguiar, AP; Jones, CN 2016 IEEE 55th Conference on Decision and Control, CDC 201 ID Authenticus: P-00M-DYJ DOI: 10.1109/cdc.2016.7798749 Abstract: This paper addresses the design of a suitable terminal set and terminal cost for discrete-time Economic Model Predictive Control schemes with…
Input-to-State-Stability Approach to Economic Optimization in Model Predictive Control
Alessandretti, A; Aguiar, AP; Jones, CN IEEE Transactions on Automatic Control ID Authenticus: P-00N-697 DOI: 10.1109/tac.2017.2700388 Abstract: This paper presents a model predictive control (MPC) scheme where a combination of a stabilizing stage cost and an economic stage cost is employed to allow…
A Nonlinear Model Predictive Control for an AUV to Track and Estimate a Moving Target Using Range Measurements
Jain, RP; Alessandretti, A; Aguiar, AP ; de Sousa, JB ROBOT 2017: Third Iberian Robotics Conference – Volume 1, Seville, Spain, November 22-24, 2017 ID Authenticus: P-00N-82A DOI: 10.1007/978-3-319-70833-1_14 Abstract: In this paper, we propose a Nonlinear Model Predictive Control (NMPC) approach that…
Model Predictive Cloud-based Control Scheme for Trajectory-Tracking: Effects of Round-trip Time Over-estimates
Andrea Alessandretti (Autor) (Outra); António Pedro Aguiar 2018 13TH APCA INTERNATIONAL CONFERENCE ON CONTROL AND SOFT COMPUTING (CONTROLO) ID Authenticus: P-00P-YAK DOI: 10.1109/controlo.2018.8516416 Abstract: This paper addresses the design and implementation of a Model Predictive Control (MPC) scheme for trajectory tracking on a…
Optimization-Based and Optimal Control
Publications on Optimization-Based and Optimal Control
Second-Order-Optimal Minimum-Energy Filters on Lie Groups
Saccon, A; Trumpf, J; Mahony, R; Aguiar, AP IEEE Transactions on Automatic Control ID Authenticus: P-00M-57F DOI: 10.1109/tac.2015.2506662 Abstract: Systems on Lie groups naturally appear as models for physical systems with full symmetry. We consider the state estimation problem for such systems where…
On convergence and Performance Certification of a Continuous-time Economic Model Predictive Control Scheme with Time-varying Performance Index
Alessandretti, A; Aguiar, AP; Jones, CN AUTOMATICA ID Authenticus: P-00K-93B DOI: 10.1016/j.automatica.2016.01.020 Abstract: This paper addresses the design of convergence and performance certified sampled-data model predictive control (MPC) laws with a time-dependent economic performance index. More precisely, using a dissipativity property of the…
On the Design of Discrete-Time Economic Model Predictive Controllers
Alessandretti, A; Aguiar, AP; Jones, CN 2016 IEEE 55th Conference on Decision and Control, CDC 201 ID Authenticus: P-00M-DYJ DOI: 10.1109/cdc.2016.7798749 Abstract: This paper addresses the design of a suitable terminal set and terminal cost for discrete-time Economic Model Predictive Control schemes with…
Design of a Distributed Quantized Luenberger Filter for Bounded Noise
Rego, FFC; Pu, Y; Alessandretti, A; Aguiar, AP; Pascoal, AM; Jones, CN 2016 AMERICAN CONTROL CONFERENCE (ACC) ID Authenticus: P-00M-HJC DOI: 10.1109/acc.2016.7526675 Abstract: This paper addresses the problem of distributed state estimation for linear systems with process and measurement noise, in the case…
Large-Scale Distributed Systems
Publications on Large-Scale Distributed Systems
An overview of structural systems theory
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…
Minimum Cost Input/Output Design for Large-scale Linear Structural Systems
Pequito, S; Kar, S; Aguiar, AP AUTOMATICA ID Authenticus: P-00K-92Z DOI: 10.1016/j.automatica.2016.02.005 Abstract: In this paper, we provide optimal solutions to two different (but related) input/output design problems involving large-scale linear dynamical systems, where the cost associated to each directly actuated/measured state variable…
A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems
Pequito, S; Kar, S; Aguiar, AP IEEE Transactions on Automatic Control ID Authenticus: P-00K-7VH DOI: 10.1109/tac.2015.2437525 Abstract: This paper addresses problems on the structural design of large-scale control systems. An efficient and unified framework is proposed to select the minimum number of manipulated/measured…
A Distributed Model Predictive Control Scheme for Coordinated Output Regulation
Alessandretti, A; Aguiar, AP 20th World Congress of the International-Federation-of-Automatic-Control (IFAC) ID Authenticus: P-00N-4YW DOI: 10.1016/j.ifacol.2017.08.1550 Abstract: This paper addresses the coordinated output regulation control problem. Consider a network of agents with associated output equations, where the latter is a function of the…
Coordinated Efficient Buoys Data Collection in Large Complex Coastal Environments using UAVs
J. Braga; F. Balampanis; Aguiar, AP; João Tasso Sousa; I. Maza; A. Ollero Proceedings of the OCEANS 2017 MTS/IEEE Anchorage, 2017 Abstract: Deploying a large number of sensing buoys is a powerful tool for oceanographic, marine biology and climate change…
Machine Learning-Based Systems
Publications on Machine Learning-Based Systems
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…
Adaptive Sampling Using an Unsupervised Learning of GMMs Applied to a Fleet of AUVs with CTD Measurements
Khoshrou, A; Aguiar, AP; Fernando Lobo Pereira ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1 ID Authenticus: P-00K-2BZ DOI: 10.1007/978-3-319-27146-0_25 Abstract: This paper addresses the problem of real-time adaptive sampling using a coordinated fleet of Autonomous Underwater Vehicles (AUVs). The…
Real-Time Outlier Detection Applied to a Doppler Velocity Log Sensor Based on Hybrid Autoencoder and Recurrent Neural Network
Davari, N; Aguiar, AP IEEE JOURNAL OF OCEANIC ENGINEERING ID Authenticus: P-00T-QWZ DOI: 10.1109/joe.2021.3057909 Abstract: This article presents a real-time outlier detection deep-learning (OD-DL)-based method using a hybridized artificial neural network (ANN) approach. We propose an unsupervised ANN scheme that runs in parallel,…
Deep Learning-Assisted Short-Term Load Forecasting Forsustainable Management of Energy in Microgrid
Arash Moradzadeh; Hamed Moayyed; Sahar Zakeri; Behnam Mohammadi-Ivatloo; António Pedro Aguiar MDPI Inventions ID Authenticus: P-00T-D3G DOI: 10.3390/inventions6010015 Abstract (EN): Nowadays, supplying demand load and maintaining sustainable energy are important issues that have created many challenges in power systems. In these types of…