Creator:
Contributor:
Korbicz, Józef - red. ; Uciński, Dariusz - red.
Title:
Supervisory predictive control and on-line set-point optimization
Group publication title:
Subject and Keywords:
predictive control ; nonlinear control ; linearization ; model uncertainty ; constrained control ; set-point optimization
Abstract:
The subject of this paper is to discuss selected effective known and novel structures for advanced process control and optimization. The role and techniques of model-based predictive control (MPC) in a supervisory (advanced) control layer are first shortly discussed. The emphasis is put on algorithm efficiency for nonlinear processes and on treating uncertainty in process models, with two solutions presented: the structure of nonlinear prediction and successive linearizations for nonlinear control, and a novel algorithm based on fast model selection to cope with process uncertaint ; Issues of cooperation between MPC algorithms and on-line steady-state set-point optimization are next discussed, including integrated approaches. Finally, a recently developed two-purpose supervisory predictive set-point optimizer is discussed, designed to perform simultaneously two goals: economic optimization and constraints handling for the underlying unconstrained direct controllers.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Date:
Resource Type:
DOI:
Pages:
Source:
AMCS, Volume 20, Number 3 (2010) ; click here to follow the link