Model-Predictive Control of an Experimental Solid Oxide Fuel Cell Stack
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In the framework of real-time optimization, measurements are used to compensate for effects of uncertainty. The main approach uses measurements to update the parameters of a process model. In contrast, the constraint-adaptation scheme uses the measurements ...
In a recent work, a frequency method based on linear programming is proposed to design fixed-order linearly parameterized controllers for stable linear multi- model SISO systems. The method is based on the shaping of the open-loop transfer functions in the ...
This work concentrates on improving the robustness of constraint solvers by increasing the propagation strength of constraint models in a declarative and automatic manner. Our objective is to efficiently identify and remove shavable values during search. A ...
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Optimization arises naturally when process performance needs improvement. This is often the case in industry because of competition – the product has to be proposed at the lowest possible cost. From the point of view of control, optimization consists in de ...
While there is a large class of Multiple-Target Tracking (MTT) problems for which batch processing is possible and desirable, batch MTT remains relatively unexplored in comparison to sequential approaches. In this paper, we give a principled probabilistic ...
A linear programming approach is proposed to tune fixed-order linearly parameterized gain-scheduled controllers for stable SISO linear parameter varying (LPV) plants. The method is based on the shaping of the open-loop transfer functions in the Nyquist dia ...
Repeated failures as well as difficulties related to the implementation of new hydroelectric powerplants in industrialized countries illustrate the paradigm evolution which manages relationship between human society and nature. Problems resulting from thes ...
he problem of designing real-time traffic signal control strategies for large-scale congested urban road networks via suitable application of control and optimization methods is considered. Three alternative methodologies are proposed, all based on the sto ...
Model predictive control (MPC) is a very effective approach to control nonlinear systems, especially when the systems are high dimensional and/or constrained. MPC formulates the problem of input trajectory generation as an optimization problem. However, du ...
This thesis deals with dynamic optimization of batch processes, i.e. processes that are characterized by a finite time of operation and the frequent repetition of batches. The objective is to maximize the quantity of the desired product at final time while ...
