@inproceedings{62d9bcd8a718400e999df83451e9261a,
title = "Optimal normalized weighting factor in iterative feedback tuning of step input responses",
abstract = "Iterative feedback tuning (IFT) is a model-free tuning method that has been proven to work well in various applications since its introduction in 1994. Several factors affect the performance of the optimization process, and one of which is the design criterion. Historically, the weighting factor for each element in the design criterion is chosen by trial and error and results in a different value for each system tested. In this paper, a normalized design criterion is presented with a weighting factor that allows the tuning performance to be assessed across different systems. This new design criterion is then applied to various test systems using the Monte Carlo method to determine the optimal range of values of this normalized weighting factor in tuning for step input responses.",
keywords = "Automatic control, Iterative methods, Monte Carlo simulation, Numerical algorithms, Self-optimizing control",
author = "Lu, \{Charles Z.\} and Xie, \{Sheng Q.\} and Chao Deng",
note = "Publisher Copyright: {\textcopyright} IFAC.; 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 ; Conference date: 24-08-2014 Through 29-08-2014",
year = "2014",
doi = "10.3182/20140824-6-za-1003.00444",
language = "英语",
series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",
publisher = "IFAC Secretariat",
pages = "4790--4795",
editor = "Edward Boje and Xiaohua Xia",
booktitle = "19th IFAC World Congress IFAC 2014, Proceedings",
}