Analysis and design of model predictive control frameworks for dynamic operation—An overview

Köhler, Johannes; Müller, Matthias A.; Allgöwer, Frank

doi:10.1016/j.arcontrol.2023.100929

Cited by 9 publications

(1 citation statement)

References 188 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This paper takes as its context Model Predictive Control (MPC) [1][2][3][4][5][6][7][8]. There have been an enormous number of papers published in this area showing how MPC algorithms can be tailored to specific objectives and requirements (e.g., [9,10]), but in the main these approaches focus on algorithms that require substantial computational power.…”

Section: Introductionmentioning

confidence: 99%

Improving the Feedforward Component for Recent Variants of Predictive Functional Control

Rossiter,

Abdullah,

Aftab

2024

Processes

View full text Add to dashboard Cite

A recent study demonstrated that the use of feedforward information with conventional Predictive Functional Control (PFC) leads to unexpected inconsistencies, with subsequent negative impacts on tuning and behaviour. A proposal was made to define the coincident point differently and shown to reduce the lag in the closed-loop PFC responses and applied to some systems with benign dynamics. Other recent work has looked at parameterisations of the future input to deal with challenging open-loop dynamics and significantly extended the range of problems for which PFC can be effective. This paper combines the two concepts, and thus proposes an algorithm that has both more effective and simple tuning than original PFC as well as being applicable to a range of challenging dynamics.

show abstract