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Found 9 papers, 0 papers with code
Decentralized PI-control and Anti-windup in Resource Sharing Networks
We consider control of multiple stable first-order systems which have a control coupling described by an M-matrix.
A Two-Layers Predictive Algorithm for Workplace EV Charging
In this paper, the problem of electric vehicle (EV) charging at the workplace is addressed via a two-layer predictive algorithm.
Anti-windup coordination strategy around a fair equilibrium in resource sharing networks
This paper aims at coordinating interconnected agents where the control input of each agent is limited by the control input of others.
Robust Switching Control of DC-DC Boost Converter for EV Charging Stations
In this work, the problem of switching control design for DC-DC boost converter is considered, in the case of operation under uncertain equilibrium condition arising due to perturbations in the input and load parameters.
Hydraulic Parameter Estimation in District Heating Networks
In this paper, a method is proposed to obtain a grey-box hydraulic model for tree-shaped district heating systems: hydraulic parameters are estimated based on pressure measurements in only two locations.
Data-driven approximation and reduction from noisy data in matrix pencil frameworks
This work aims at tackling the problem of learning surrogate models from noisy time-domain data by means of matrix pencil-based techniques, namely the Hankel and Loewner frameworks.
Combating District Heating Bottlenecks Using Load Control
This increases the effect of the already existing issue of hydraulic bottlenecks, causing peripheral units (customers) to experience reduced flow rates.
Learning-based hierarchical control of water reservoir systems
The optimal control of a water reservoir systems represents a challenging problem, due to uncertain hydrologic inputs and the need to adapt to changing environment and varying control objectives.
Data-driven control of infinite dimensional systems: Application to a continuous crystallizer
Controlling infinite dimensional models remains a challenging task for many practitioners since they are not suitable for traditional control design techniques or will result in a high-order controller too complex for implementation.
