Performance assessment of constrained model predictive control systems
β Scribed by Byung-Su Ko; Thomas F. Edgar
- Publisher
- American Institute of Chemical Engineers
- Year
- 2001
- Tongue
- English
- Weight
- 163 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0001-1541
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β¦ Synopsis
Abstract
A constrained minimum variance controller is derived based on a moving horizon approach that explicitly accounts for hard constraints on process variables. A procedure for the performance assessment of constrained model predictive control systems is then developed based on the constrained minimum variance controller. The performance bound computed using the proposed moving horizon approach converges to the unconstrained minimum variance performance bound when the constraints on process variables become inactive. The utility of the proposed method in the performance assessment of constrained model predictive control systems is demonstrated through a simulated example.
π SIMILAR VOLUMES
Generalized predictive control (GPC) and dynamic performance predictive control (DPC) algorithms are introduced for industrial applications. Constraints on plant input rate, plant absolute input and plant absolute output can be implemented and are demonstrated on an application of these algorithms.