Conference paper
Improving Convergence of Iterative Feedback Tuning using Optimal External Perturbations
Computer Aided Process Engineering Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark1
Department of Chemical and Biochemical Engineering, Technical University of Denmark2
Mathematical Statistics, Department of Informatics and Mathematical Modeling, Technical University of Denmark3
Department of Informatics and Mathematical Modeling, Technical University of Denmark4
Iterative feedback tuning constitutes an attractive control loop tuning method for processes in the absence of sufficient process insight. It is a purely data driven approach to optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient, which is used in a search algorithm.
A slow rate of convergence of the tuning method is often experienced when tuning for disturbance rejection. This is due to a poor signal to noise ratio in the process data. A method is proposed for increasing the information content in data by introducing an optimal perturbation signal in the tuning algorithm.
For minimum variance control design the optimal design of an external perturbation signal is derived in terms of the asymptotic accuracy of the iterative feedback tuning method.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2008 |
| Pages: | 2618-2623 |
| Proceedings: | 47th IEEE Conference on Decision and Control |
| ISBN: | 1424431239 , 9781424431236 , 1424431247 and 9781424431243 |
| ISSN: | 01912216 |
| Types: | Conference paper |
| DOI: | 10.1109/CDC.2008.4738785 |
| ORCIDs: | Huusom, Jakob Kjøbsted , Poulsen, Niels Kjølstad and Jørgensen, Sten Bay |
Control design Convergence Cost function Feedback loop Iterative algorithms Iterative methods Optimal control Shape control Signal design Signal processing asymptotic accuracy control loop tuning method control system synthesis disturbance rejection external perturbation signal feedback iterative feedback tuning iterative methods loop performance cost function gradient minimum variance control design optimal design optimal external perturbations optimal perturbation signal perturbation techniques search algorithm search problems signal processing signal to noise ratio standard formulation sufficient process insight tuning unbiased estimate
