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The distribution networks are experiencing important changes driven by the massive integration of renewable energy conversion systems. However, the lack of direct controllability of the Distributed Generations (DGs) supplying Active Distribution Networks ( ...
The desire to operate chemical processes in a safe and economically optimal way has motivated the development of so-called real-time optimization (RTO) methods [1]. For continuous processes, these methods aim to compute safe and optimal steady-state set ...
This thesis studies the automatic design and optimization of high-performing robust controllers for mobile robots using exclusively on-board resources. Due to the often large parameter space and noisy performance metrics, this constitutes an expensive opti ...
Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not ...
Solving a multi-input dynamic optimization of a batch processes is a complex problem involving interactions between input variables and constraints over time. The problem gets more difficult due to the presence of local solutions that have almost the same ...
This work examines the performance of stochastic sub-gradient learning strategies, for both cases of stand-alone and networked agents, under weaker conditions than usually considered in the literature. It is shown that these conditions are automatically sa ...
Small-scale turbomachines in domestic heat pumps reach high efficiency and provide oil-free solutions, which improve heat-exchanger performance and offer major advantages in the design of advanced thermodynamic cycles. An appropriate turbocompressor for do ...
We use Isogeometric Analysis as a framework for NURBS-based shape optimization of hydrofoils. We present geometrical representations by NURBS and some of their properties to design an hydrofoil. Then, we consider an irrotational flow around an hydrofoil an ...
Many emerging nanotechnologies realize majority gates as primitive building blocks and they benefit from a majority-based synthesis. Recently, Majority-Inverter Graphs (MIGs) have been introduced to abstract these new technologies. We present optimi ...
We consider the problem of dictionary learning over large scale models, where the model parameters are distributed over a multi-agent network. We demonstrate that the dual optimization problem for inference is better conditioned than the primal problem and ...