Model Predictive Control (MPC) has emerged as a leading strategy in advanced process control, offering the ability to anticipate future process behaviour and manage constraints in dynamic systems.

Economic Model Predictive Control (EMPC) represents an evolution of traditional control strategies, where the primary objective is to directly optimise an economic cost function rather than merely ...

Distributed model predictive control (DMPC) offers a computationally efficient alternative to centralized model predictive control (CMPC) for enabling the optimal control of industrial process systems ...

Leila Bridgeman is steadily laying foundations for the software needed to precisely control the large, complex networks of ...

Distillation columns are extensively deployed in the chemical process industries when there is a need for separation of components that have different boiling points. Typically, a mixture of ...

The air conditioner compressor motor driver as shown in Fig.1 utilizes advanced model-free predictive control technology, ensuring efficient and stable operation under varying load conditions.

C reators of the iconic iRonCub3 have introduced a new control method that helps the jet-powered humanoid robot stay stable ...

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 ...

The operating profiles of traditional generators has changed to manage the variability of renewable resources. Several critical processes were not engineered to manage these highly variable operating ...

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 ...