Model Predictive Control (MPC) has emerged as a pivotal strategy for optimising the performance of power electronic converters and motor drive systems. By utilising an explicit model of the controlled ...

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 ...

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 ...

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 ...

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 ...

Electrical machines consume nearly half of all the electrical power generated worldwide, making them one of the top contributors to carbon dioxide emissions. If we are to develop sustainable societies ...

Learn to apply control systems in automotive, energy, aerospace, robotics, and manufacturing sectors. Apply feedback control laws to stabilize systems and achieve performance goals. Control systems ...

Image of digital twin control, in which real plasma is controlled by virtual plasma reproduced on a computer. In this research, we developed a digital twin control system that can estimate optimal ...

Distributed control systems are powerful assets for new and modernized power plants. Thanks to three product generations of technology innovations, these systems now provide new benefits — including ...