Abstract: This paper addresses the intricate challenges in stabilizing nonlinear systems amidst event-triggering and switching dynamics, operating under a less stringent input-to-state stability (ISS) ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Abstract: Although numerous results exist on the control of nonlinear systems subject to either tracking error constraints or full-state constraints, most of them can ...

ROS System, Hospital Drug Delivery Robot, Autonomous Localization, Path Planning, Navigation Simulation Cheng, B. and Zhang, B.Y. (2025) Research on Autonomous Localization and Navigation Simulation ...

A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how ...

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology.

This new AI acts like a digital scientist, turning messy data into simple rules that explain how the world really works.

Nonlinear systems and networks theory is a branch of automatic control theory. It takes systems and networks described by nonlinear differential equations or difference equations as its research ...

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 ...