Object structure

Title:

Supervisory predictive control and on-line set-point optimization

Group publication title:

AMCS, Volume 20 (2010)

Creator:

Tatjewski, Piotr

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

Contributor:

Korbicz, Józef - red. ; Uciński, Dariusz - red.

Date:

2010

Resource Type:

artykuł

DOI:

10.2478/v10006-010-0035-1

Pages:

483-495

Source:

AMCS, Volume 20, Number 3 (2010)

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego