Abstract
This paper describes, in tutorial fashion, an integrated identification and control design methodology that begins with dynamic modelling from plant data and concludes with parameter settings for high performance PID controllers. By integrating identification with PID controller design, the method displays functionality that is often demanded by the practicing engineering community. The major steps in this integrated methodology are: experimental design, high-order ARX estimation, and control-relevant model reduction leading to models that comply with the MC-PID tuning rules. When a persistently exciting input is applied, high-order ARX model estimation is consistent, which makes it an attractive intermediate model for control-relevant model reduction purposes; furthermore, the low computational effort associated with ARX estimation means that simple statistical tools (such as cross validation) can be used to efficiently determine a suitable structure for the ARX model without substantial user intervention. The methodology is illustrated for the case of a delayed plant subject to a disturbance displaying significant drift.
Translated title of the contribution | A methodology for integrated system identification with IMC-PID controller design |
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Original language | Spanish |
Pages (from-to) | 5-18+129 |
Journal | RIAI - Revista Iberoamericana de Automatica e Informatica Industrial |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - Oct 2007 |
Keywords
- Control-relevant modelling
- Internal Model Control (IMC)
- Model reduction
- PID control
- System identification
ASJC Scopus subject areas
- Control and Systems Engineering
- General Computer Science