2 citations · 3 across the 6 of their papers we have counts for
6 papers
Adaptive Neural-Operator Backstepping Control of a Benchmark Hyperbolic PDE
Maxence Lamarque, Luke Bhan, Yuanyuan Shi +1
To stabilize PDEs, feedback controllers require gain kernel functions, which are themselves governed by PDEs. Furthermore, these gain-kernel PDEs depend on the PDE plants' function…
Contributions of Individual Generators to Nodal Carbon Emissions
Yize Chen, Deepjyoti Deka, Yuanyuan Shi
Recent shifts toward sustainable energy systems have witnessed the fast deployment of carbon-free and carbon-efficient generations across the power networks. However, the benefits…
Deriving Loss Function for Value-oriented Renewable Energy Forecasting
Yufan Zhang, Honglin Wen, Yuexin Bian +1
Renewable energy forecasting is the workhorse for efficient energy dispatch. However, forecasts with small mean squared errors (MSE) may not necessarily lead to low operation costs…
Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees
Wenqi Cui, Yan Jiang, Baosen Zhang +1
We study the optimal control of multiple-input and multiple-output dynamical systems via the design of neural network-based controllers with stability and output tracking guarantee…
Neural Operators of Backstepping Controller and Observer Gain Functions for Reaction-Diffusion PDEs
Miroslav Krstic, Luke Bhan, Yuanyuan Shi
Unlike ODEs, whose models involve system matrices and whose controllers involve vector or matrix gains, PDE models involve functions in those roles functional coefficients, depende…
Neural Operators for Bypassing Gain and Control Computations in PDE Backstepping
Luke Bhan, Yuanyuan Shi, Miroslav Krstic
We introduce a framework for eliminating the computation of controller gain functions in PDE control. We learn the nonlinear operator from the plant parameters to the control gains…