Review on model predictive control: an engineering perspective

Abstract Model-based predictive control (MPC) describes a set of advanced control methods, which make use of a process model to predict the future behavior of the controlled system. Additionally, we provide detailed discussion on implantation details in general and strategies to cope with the computational burden—still a major factor in the design of MPC.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 By solving a—potentially constrained—optimization problem, MPC determines the control law implicitly.
• 2 This shifts the effort for the design of a controller towards modeling of the to-be-controlled process.
• 3 Since such models are available in many fields of engineering, the initial hurdle for applying control is deceased with MPC.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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