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Vicenç Puig

Researcher at Spanish National Research Council

Publications -  698
Citations -  11271

Vicenç Puig is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Fault detection and isolation & Model predictive control. The author has an hindex of 45, co-authored 656 publications receiving 9039 citations. Previous affiliations of Vicenç Puig include University of Huelva & Politehnica University of Bucharest.

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Journal ArticleDOI

Suboptimal Hybrid Model Predictive Control: Application to Sewer Networks

TL;DR: It is shown that in realistic scenarios concerning control of large scale sewer networks, depending on the value of parameters related to the mode sequence constraints (MSC), drastic reductions can be achieved in optimization time.
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Multi-layer model predictive control of inland waterways with continuous and discrete actuators

TL;DR: A three-layer control strategy to regulate the water levels in inland waterways takes into account the tidal period, which defines two different operating modes and solves an optimization problem that yields the scheduling of a set of discrete actuators that best approximates the optimal reference.
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Impact of External Disturbance and Discontinuous Input on the Redundant Manipulator Robot Behaviour using the Linear Parameter Varying Modelling Approach

TL;DR: Numerical simulations with several tasks show that in presence of mass load variation the desired trajectory is more efficiently followed by the LPV model than the dynamic model of the studied mechanism.
Proceedings ArticleDOI

Robust state estimation and fault detection combining unknown input observer and set-membership approach

TL;DR: In this paper, the authors proposed a robust state estimation and fault detection method by combining the unknown input observer (UIO) and the set-membership estimator (SME).
Proceedings ArticleDOI

Temporal/spatial model-based fault diagnosis vs. Hidden Markov models change detection method: Application to the Barcelona water network

TL;DR: A comparison of two different fault diagnosis frameworks based on a temporal/spatial model-based analysis by exploiting a-priori information about the system under study is examined by using a dataset coming from the Barcelona water transport network.