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280 results on '"Puig, Vicenc"'

1. A model predictive scheduling strategy for coordinated inland vessel navigation and bridge operation

Author

Segovia Castillo, P. (author), Puig, Vicenc (author), Reppa, V. (author), Segovia Castillo, P. (author), Puig, Vicenc (author), and Reppa, V. (author)

Abstract

This paper presents the design of a model predictive scheduling strategy to address the inland waterborne transport (IWT) problem considering bridges that must open to enable vessel passage. The main contribution is the formulation of a control-oriented model of the problem, including propositional logic expressions that characterize system behavior and their conversion into (in)equality constraints. The resulting model is embedded into a predictive scheduling approach to determine bridge opening timetables and vessel passage times in a coordinated manner. The effectiveness of the strategy is demonstrated on a realistic case study based on the Rhine-Alpine corridor., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport Engineering and Logistics

Published
2023
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4. A Nonlinear Model Predictive Control Strategy for Autonomous Racing of Scale Vehicles

Author

Cataffo, Vittorio, Silano, Giuseppe, Iannelli, Luigi, Puig, Vicenc, Glielmo, Luigi, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, and Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control

Subjects
FOS: Computer and information sciences, Autonomous vehicle navigation, Computer Science - Robotics, Informàtica::Automàtica i control [Àrees temàtiques de la UPC], Control predictiu, Autonomous racing, F1/10 simulator, Predictive control, Automobiles -- Navigation systems, Nonlinear model predictive control, Automòbils -- Sistemes de navegació, Robotics (cs.RO)
Abstract

A Nonlinear Model Predictive Control (NMPC) strategy aimed at controlling a small-scale car model for autonomous racing competitions is presented in this paper. The proposed control strategy is concerned with minimizing the lap time while keeping the vehicle within track boundaries. The optimization problem considers both the vehicle's actuation limits and the lateral and longitudinal forces acting on the car modeled through the Pacejka's magic formula and a simple drivetrain model. Furthermore, the approach allows to safely race on a track populated by static obstacles generating collision-free trajectories and tracking them while enhancing the lap timing performance. Gazebo simulations using the F1/10 simulator showcase the feasibility and validity of the proposed control strategy. The code is released as open-source making it possible to replicate the obtained results., 6 pages, 8 figures, conference

Published
2022

7. MPC-based optimal parameter scheduling of LPV controllers: Application to Lateral ADAS Control

Author

Medero, Ariel, Menezes Morato, Marcelo, Puig, Vicenc, Sename, Olivier, Menezes Morato, Marcelo, and IDEX UGA - - UGA2015 - ANR-15-IDEX-0002 - IDEX - VALID

Subjects
[SPI.AUTO] Engineering Sciences [physics]/Automatic
Abstract

In this paper, we propose an optimal online tuning scheme for design-related scheduling parameters of adaptive Linear Parameter Varying (LPV) control systems. Specifically, the method is conceived within the Model Predictive Control (MPC) framework, which we demonstrate to ensure an inputto-state stable closed-loop and a recursively feasible optimisation program. The major advantage of the proposed solution is that it automatically determines the LPV scheduling parameters online, without the need to for the designer to develop any scheduling function (which is often a repetitive and obscure task). Moreover, it offers a direct and simple tuning procedure, able to directly incorporate multi-objective performance goals into a single quadratic cost. The proposed method is tested for an LPV Advanced Driver Assistance System, showing enhanced performances when compared to state-of-the-art methods based on nonlinear scheduling functions.

Published
2022

12. Dual-Rate Control Framework With Safe Watermarking Against Deception Attacks.

Author

Bessa, Iury, Trapiello, Carlos, Puig, Vicenc, and Palhares, Reinaldo Martinez

Subjects
WATERMARKS, DECEPTION, CYBER physical systems, PLANT performance, COINCIDENCE, SECURITY systems
Abstract

This article presents a novel secure-control framework against sensor deception attacks. The vulnerability of cyber-physical systems with respect to sensor deceptive attacks makes that all sensor measurements are not reliable until the system security is assured by an attack detection module. Most of the active attack detection strategies require some time to assess the system security, while injecting a watermark signal to ease the detection. However, the injection of watermark signals deteriorates the performance and stability of the plant. The proposed control framework consists of a dual-rate control (DRC) that is able to stabilize the plant using: 1) a model predictive controller that operates at a slower sampling time; 2) a state-feedback predictor-based controller that operates in the nominal sampling time disregarding the use of the untrustworthy measurements until the attack detector is able to certify the security; and 3) a reconfiguration block (RB) for palliating the effect of the watermarking. Simulation results indicate the efficacy of the proposed DRC framework to defend the system from cyber-attacks and the ability of the RB to improve the closed-loop performance during the watermark injection. [ABSTRACT FROM AUTHOR]

Published
2022
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35. Leak Localization Method for Water-Distribution Networks Using a Data-Driven Model and Dempster–Shafer Reasoning.

Author

Soldevila, Adria, Blesa, Joaquim, Jensen, Tom Norgaard, Tornil-Sin, Sebastian, Fernandez-Canti, Rosa M., and Puig, Vicenc

Subjects
PRESSURE sensors, DEMPSTER-Shafer theory, PRESSURE measurement, FLOW measurement, ESTIMATION theory
Abstract

This article presents a new data-driven method for leak localization in water-distribution networks (WDNs). The method uses the information provided by a set of pressure sensors installed in some internal network nodes in addition to flow and pressure measurements from inlet nodes. Pressure measurements are recorded under leak-free network operation, and a WDN data-driven model of the pressure at each sensed node is adjusted. The pressure estimation from this model is complemented by a Kriging spatial interpolation technique to estimate the pressure in the nodes that are not sensed, leading to a pressure reference map. Leak localization is based on the comparison of this reference pressure map with the current pressure map that is obtained by applying Kriging directly to the pressure measurements provided by sensors. The key element in this comparison is the use of the Dempster–Shafer theory for reasoning under uncertainty. The successful application of the proposed methodology to two real-data case studies is presented. [ABSTRACT FROM AUTHOR]

Published
2021
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