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A design algorithm using external perturbation to improve Iterative Feedback Tuning convergence
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DOI：10.1016/j.automatica.2011.05.029.png)
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摘要
En 中文
Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of process insight. It is a purely data driven approach for 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 for minimizing the performance cost. 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 data information content by introducing an optimal perturbation signal in the tuning algorithm. The theoretical analysis is supported by a simulation example where the proposed method is compared to an existing method for acceleration of the convergence by use of optimal prefilters. (C) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Controller tuning
Direct tuning
Iterative schemes
Iterative Feedback Tuning
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期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
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