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Found 5 papers, 1 papers with code
Physics-informed Neural Network Modelling and Predictive Control of District Heating Systems
This paper addresses the data-based modelling and optimal control of District Heating Systems (DHSs).
Nonlinear MPC design for incrementally ISS systems with application to GRU networks
This brief addresses the design of a Nonlinear Model Predictive Control (NMPC) strategy for exponentially incremental Input-to-State Stable (ISS) systems.
Deep Long-Short Term Memory networks: Stability properties and Experimental validation
The aim of this work is to investigate the use of Incrementally Input-to-State Stable ($\delta$ISS) deep Long Short Term Memory networks (LSTMs) for the identification of nonlinear dynamical systems.
An incremental input-to-state stability condition for a generic class of recurrent neural networks
This paper proposes a novel sufficient condition for the incremental input-to-state stability of a generic class of recurrent neural networks (RNNs).
Hierarchical Control in Islanded DC Microgrids with Flexible Structures
Hierarchical architectures stacking primary, secondary, and tertiary layers are widely employed for the operation and control of islanded DC microgrids (DCmGs), composed of Distribution Generation Units (DGUs), loads, and power lines.
