Model Parameterization Tailored to Real-Time Optimization
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Optimization is important in science and engineering as a way of finding ”optimal” situations, designs or operating conditions. Optimization is typically performed on the basis of a mathematical model of the process under investigation. In practice, optimi ...
The current context leads energy system design to very demanding objectives, due to their variety. Indeed, despite an increasing energy demand, environment indicators are becoming always more important. So that for a given service, emission (and then assoc ...
This thesis is about the numerical simulation and optimization of the alumina repartition in the bath of an aluminium electrolysis pot. A mathematical model is set up which contains the feeding of alumina particles to the bath, the dissolution of the parti ...
Reverse convex programming (RCP) represents an important class of global optimization problems consisting of concave cost and inequality constraint functions. While useful in many practical scenarios due to the frequent appearance of concave models, a more ...
The operation of dynamic processes can be optimized using models that predict the system behavior well, in particular its optimality features. In practice, however, process models are often structurally inaccurate, and on-line adaptation is typically requi ...
Current superstructure size for energy system design is increasing with computing facility improvement. Despite such approach allows to link and to analyse a lot of elements, demonstrating the advantage of a global optimization, non-negligible uncertaintie ...
This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...
We consider differentiability with respect to the switch times of the value function of an optimal control problem for a non-autonomous switched system. The control variables are the switch times between the modes and the input in each mode. We provide a m ...
This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...
Temporal networks describe workflows of time-consuming tasks whose processing order is constrained by precedence relations. In many cases, the durations of the network tasks can be influenced by the assignment of resources. This leads to the problem of sel ...
