Model Predictive Control Design for f Nonlinear Four-Tank System
In recent years, MPC has become a prominent advanced control technique, especially in large industrial processes. However, for enormous complexity, non-convexity and computational reasons, MPC practice and applications have been restricted to linear plants. During the last decade, many formulatio...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English |
| Published: |
2008
|
| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/7299/1/FK_2008_86a.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In recent years, MPC has become a prominent advanced control technique, especially in
large industrial processes. However, for enormous complexity, non-convexity and
computational reasons, MPC practice and applications have been restricted to linear
plants. During the last decade, many formulations have been developed for MPC
formulation of linear and nonlinear, stable and unstable plants but still there remain
some unsolved issues which depend on plant specifications. Instability, unfeasibility,
non-convexity and lack of robustness are examples of unsolved issues.
In this thesis a control system has been designed for a highly nonlinear and non minimum
phase Four-Tank system. Then constrained optimization is employed in the
MPC formulation to repair violation on boundaries. It also leads the system to work with
the best performance. Additionally, the influence of most effective tuning parameters in
MPC strategy has been investigated. In particular main part of the thesis has focused on
performance criteria based on good reference tracking in model predictive control domain. Regarding to investigate the performance of this algorithm and due to
application of “nonlinear Four-Tank system” in control theory and industry, this system
is considered as a plant to be examined under this method. The most attractive aspect of
this system is; the time-varying movement of a right half plane transmission zeros across
the imaginary axis. This system’s configuration makes the process difficult to control
under the previous controllers. This problem appears to be one of the most important and
practical designs of nonlinear system in process control.
In this thesis, besides good performance, the algorithm enjoys from relative simplicity
and faster response in compare with the algorithms developed in other previous works.
The problems of complexity of algorithm, non-convexity of the optimization, especially
when working with nonlinear plants are the most common problems in the control
design criteria. Since linear model predictive control is used instead of nonlinear model
predictive control; these problems are avoided to be appeared in this work. All the
results in this study show fast performance in controlling the Four-Tank system. Both of
the weighting matrices are considered so that a system is fast enough smooth control
signals and they are tuned till the desired performance is achieved.. Low value of
prediction horizon and weighting matrices are more preferable to reduce number of free
variable and avoid complexity of analysis. |
|---|