IEEE

Approximate Nonlinear Model Predictive Control With Safety-Augmented Neural Networks

Abstract: Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies ...
Frontiers

Looking at both sides of algorithmic control and employee well-being: a job demands−resources model

Drawing on the job demands-resources (JD-R) theory, this study aims to analyze the impact of algorithmic control on the well-being of delivery drivers by focusing on the mediating role of job demands ...
Harvard Medical School

New Artificial Intelligence Model Could Speed Rare Disease Diagnosis

A new AI model called popEVE can predict how likely each variant in a patient’s genome is to cause disease. The team is testing popEVE in clinical settings to see if it can speed accurate diagnoses of ...
EurekAlert!

Model-based control of a continuum manipulator with online Jacobian error compensation using Kalman filtering

(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...
C&EN

Long-Term Coexposure to Multiple Air Pollutants and Stroke Incidence: A Large Prospective Cohort Study Based on a Shape-Constrained Nonlinear Weighted-Sum Model

National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China ...
Automation

Addressing the Myths of Model Predictive Control (MPC)

Manufacturers have taken notice, and many more are implementing MPC into their plants and reaping benefits.Can MPC completely displace PID in a control engineer’s toolbox? Of course not. There are ...