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Found 4 papers, 1 papers with code
Preemptive Scheduling of EV Charging for Providing Demand Response Services
We develop a new algorithm for scheduling the charging process of a large number of electric vehicles (EVs) over a finite horizon.
A New Data-Driven Sparse-Learning Approach to Study Chemical Reaction Networks
In this paper, we introduce a novel approach for the identification of the influential reactions in chemical reaction networks for combustion applications, using a data-driven sparse-learning technique.
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
In this paper, we propose an optimization-based sparse learning approach to identify the set of most influential reactions in a chemical reaction network.
Guaranteed Model-Based Fault Detection in Cyber-Physical Systems: A Model Invalidation Approach
This paper presents a sound and complete fault detection approach for cyber-physical systems represented by hidden-mode switched affine models with time varying parametric uncertainty.
Optimization and Control
