We're a long way from having extensive powers of crime prediction, but that's not to say that it makes no sense to consider ...

This study presents a predictive control system for the operation speed of combine harvesters, integrating multi-sensor fusion and deep learning techniques. The EKF integrates IMU and BDS/GPS signals ...

In this article, we present an implementation of a low-memory footprint model predictive control (MPC)-based controller in programmable logic controllers (PLCs). Automatic code generation of ...

An artificial-intelligence model did something last month that no machine was ever supposed to do: It rewrote its own code to avoid being shut down. Nonprofit AI lab Palisade Research gave OpenAI ...

Model predictive control (MPC) has emerged as a promising strategy to address these challenges effectively since its inception. In this study, MPC is applied to optimize indoor performance by ...

Model Predictive Control (MPC) is a widely used optimization-based control strategy for constrained systems. MPC relies on the repeated online solution of an optimal control problem, which determines ...

1. Introduction 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 ...

By shifting majority of the computational effort off-line, the concept of explicit MPC offers a significantly faster and cheaper implementation of model predictive control. We show how explicit MPC ...

This project is source code of paper Deep DeePC: Data-enabled predictive control with low or no online optimization using deep learning by X. Zhang, K. Zhang, Z. Li, and X. Yin. The objective of this ...