AUTOMATED CONTROL FOR A PHYSICAL SYSTEM WITH GENERIC FORECASTING MODELS

Abstract: one or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to automated control for a physical system with generic forecasting models. the computer-implemented system can comprise a memory that can store computer executable components. the computer-implemented system can further comprise a processor that can execute the computer executable components stored in the memory, wherein the computer executable components can comprise a training component that trains one or more multivariate time series forecasting models, and a prediction component that forecasts long-horizon action trajectories for a set of state variables over a defined range of time. furthermore, an analysis component can linearize the state-based action response model, wherein the linearized the state-based action response model can be formulated into an milp optimization problem and solved to obtain a multi-step set-point recommendation.

Inventor(s): Dung Tien Phan, Sumanta Mukherjee, Pankaj Satyanarayan Dayama, Jayant R. Kalagnanam

CPC Classification: G06N20/00 (Machine learning)

Search for rejections for patent application number 20250217698