Journal article
A multiple model, state feedback strategy for robust control of non-linear processes
Computers & Chemical Engineering, Vol.31(5-6), pp.410-418
05/2007
Abstract
The major limitation of reported multiple model approaches is that robustness against process/controller disturbances cannot be addressed for processes consisting of hybrid stable/unstable regimes, or with chaotic dynamics. In this paper, a significantly modified multiple model approach is developed to achieve robust control with global stability. The new advances include: (1) stabilization of open-loop unstable plants using a state feedback strategy, (2) incorporation of an adjustable pre-filter to achieve offset-free control, (3) implementation of a Kalman filter for state estimation, and (4) connection of the multiple model approach with non-linear model predictive control to achieve a precise control objective. The improved controller design method is successfully applied to two non-linear processes with different chaotic behaviour. Compared with conventional methods without model modifications, the new approach has achieved significant improvement in control performance and robustness with a dramatically reduced number of local models.
Details
- Title
- A multiple model, state feedback strategy for robust control of non-linear processes
- Authors/Creators
- F.Y. Wang (Author/Creator) - The University of QueenslandP.A. Bahri (Author/Creator) - Murdoch UniversityP.L. Lee (Author/Creator) - University of South AustraliaI.T. Cameron (Author/Creator) - The University of Queensland
- Publication Details
- Computers & Chemical Engineering, Vol.31(5-6), pp.410-418
- Publisher
- Elsevier
- Identifiers
- 991005541466107891
- Copyright
- © 2006 Elsevier Ltd. All rights reserved.
- Murdoch Affiliation
- School of Engineering
- Language
- English
- Resource Type
- Journal article
- Note
- ESCAPE-15 — Selected Papers from the 15th European Symposium on Computer Aided Process Engineering held in Barcelona, Spain, May 29-June 1, 2005.
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InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.29 Automation & Control Systems
- 4.29.30 Robust Control Systems
- Web Of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Chemical
- ESI research areas
- Chemistry