5 papers
Transmission Neural Networks: Approximate Receding Horizon Control for Virus Spread on Networks
Shuang Gao, Peter E. Caines
Transmission Neural Networks (TransNNs) proposed by Gao and Caines (2022) serve as both virus spread models over networks and neural network models with tuneable activation functio…
Transmission Neural Networks: Approximation and Optimal Control
Shuang Gao, Peter E. Caines
Transmission Neural Networks (TransNNs) introduced by Gao and Caines (2022) connect virus spread models over networks and neural networks with tuneable activation functions. This p…
Optimal and Approximate Solutions to Linear Quadratic Regulation of a Class of Graphon Dynamical Systems
Shuang Gao, Peter E. Caines
In this paper we study the linear quadratic regulation (LQR) problem for dynamical systems coupled over large-scale networks and obtain locally computable low-complexity solutions.…
Spectral Representations of Graphons in Very Large Network Systems Control
Shuang Gao, Peter E. Caines
Graphon-based control has recently been proposed and developed to solve control problems for dynamical systems on networks which are very large or growing without bound (see Gao an…
Graphon Control of Large-scale Networks of Linear Systems
Shuang Gao, Peter E. Caines
To achieve control objectives for extremely large-scale complex networks using standard methods is essentially intractable. In this work a theory of the approximate control of comp…