Abstract Model predictive control (MPC) is widely accepted as a generic multivariable
controller with constraint handling. More recently, MPC has been extended to nonlinear …

Crystallization, as a solid–liquid separation process, is employed to purify and isolate a
great diversity of crystalline pharmaceutical products. In recent years, continuous …

Advanced model-based control methods have been widely used in industrial process
control, but excellent performance requires regular maintenance of its model. Reinforcement …

Scenario-based model predictive control (MPC) methods introduce recourse into optimal
control and can thus reduce the conservativeness inherent to open-loop robust MPC …

Since last 40 years, the theory and technology of model predictive control (MPC) have been
developed rapidly. However, nonlinear MPC still faces difficulties such as high online …

Planning a regional energy system based on the advantages of different types of energies
and building an economic and efficient regional integrated energy system (RIES) are hot …

Key requirements for robust nonlinear model predictive control (NMPC) are stability, efficient
performance under uncertainty, constraint satisfaction and computational efficiency …

Distillation is one of the most studied processes in the control literature because of its
importance as a separation process. However, little attention has been paid to the dynamics …

Hydraulic fracturing has gained increasing attention as it allows the constrained natural gas
and crude oil to flow out of low‐permeability shale formations and significantly increase …

The robustness, degree of conservativeness, and computational efficiency in robust multi-
stage MPC are affected by scenario selection. This study explores the advantages of …