This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

Dynamic AI systems applied in biopharmaceutical manufacturing must be governed within established regulatory frameworks.

Abstract: In this article, we establish a collection of new theoretical properties for nonlinear stochastic model predictive control (SMPC). Based on the concept of stochastic input-to-state stability ...

Researchers developed a continuous-time AI framework for adaptive energy control across multi-zone building profiles using ...

Abstract: In past robotics applications, Model Predictive Control (MPC) has often been limited to linear models and relatively short time horizons. In recent years however, research in optimization, ...

Production plans at oil refineries do not always survive contact with the plant floor. Changes in feedstock quality, ...

Dr. Alex Fedoseyev, Director of Research at Ultra Quantum Inc., explores a new paradigm for turbulence modelling known as the ...

Integrating plant biosensors, IoT, and AI transforms precision agriculture, enhancing crop monitoring and resource efficiency ...

McGill researchers have found that dangerous crowd conditions leading to surges and stampedes may not emerge suddenly but ...

Spread the love“`html The world of personal finance is on the cusp of a seismic shift, and if you haven’t been paying ...

Laser-driven fields directly control transverse kinetic instabilities and, through nonlinear coupling, delay longitudinal ...

Recent progress in materials, flexible sensors, and embedded intelligence has significantly accelerated the development of ...