Applying model-predictive methods and a continuous process-control framework to a continuous tablet-manufacturing process. Currently, there is a high level of interest in the pharmaceutical industry ...

Predictive control techniques, particularly Model Predictive Control (MPC), have emerged as a transformative solution in the management of irrigation canal systems. These methods allow for the ...

Stochastic Model Predictive Control (SMPC) for linear systems is an advanced control framework that blends systematic optimisation with probabilistic forecasting. By explicitly accounting for ...

Abstract: This article explores the design of a broad learning system-based model predictive control for nonlinear industrial cyber-physical systems. BLS model is initially trained from data which is ...

Abstract: This paper investigates the distributed consensus control problem for linear multiagent systems with unknown system parameters. First, a time-varying estimation system is designed to ...

Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...

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 ...

The enhanced plant performance achieved at the 1,477-MW Morgantown Generating Station shows the value of model predictive control in conjunction with intelligent distributed control algorithms. This ...

To improve the dynamic response performance of a high-flow electro-hydraulic servo system, scholars have conducted considerable research on the synchronous and time-sharing controls of multiple valves ...

A new technique able to forecast how changes to parameters will impact biomanufacturing processes could revolutionize drug production, save manufacturers time and money, and help increase access to ...