Methodologie d'Optimisation Dynamique et de Commande Optimale des Petites Stations d'Epuration a Boues Activees
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Fast model predictive control on embedded sys- tems has been successfully applied to plants with microsecond sampling times employing a precomputed state-to-input map. However, the complexity of this so-called explicit MPC can be prohibitive even for low-d ...
This report is intended to summarize the work of a semester project conducted on a gPROMS model (developed in LENI) of an existing stand-alone 1kW solid oxide fuel cell (SOFC) system. Different means of controlling the cathode gas temperature with single-i ...
A model predictive control law is given by the solution to a parametric optimization problem that can be pre- computed offline and provides an explicit map from state to control input. In this paper, an algorithm is introduced based on wavelet multiresolut ...
Institute of Electrical and Electronics Engineers2011
In Model Predictive Control, the enforcement of hard state constraints can be overly conservative or even infeasible, especially in the presence of disturbances. This work presents a soft constrained MPC approach that provides closed- loop stability even f ...
In model reference control, the objective is to design a controller such that the closed-loop system resembles a reference model. In the standard model-based solution, a plant model replaces the unknown plant in the design phase. The norm of the error betw ...
Recent research has proposed mainstream traffic flow control (MTFC), enabled via variable speed limits (VSLs), as a novel motorway traffic management tool and has demonstrated its efficiency based on sophisticated optimal control methods that may face diff ...
Institute of Electrical and Electronics Engineers2011
This article presents an algorithm for robust nonlinear explicit model predictive control. A low complexity receding horizon control law is obtained by approximating the optimal control law using multiscale basis function approximation. Feasibility and inp ...
A model predictive control law (MPC) is given by the solution to a parametric optimization problem that can be pre-computed offline, which provides an explicit map from state to input that can be rapidly evaluated online. However, the primary limitations o ...
This paper looks at the efficiency of the parame- terisation of the degrees of freedom within an optimal predictive control algorithm. It is shown that the conventional approach of directly determining each individual future control move is not efficient i ...
Some frequency-domain controller design problems are solved using a finite number of frequency samples. Consequently, the performance and stability conditions are not guaranteed for the frequencies between the frequency samples. In this paper, all possible ...
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