@inproceedings{edacdef6cfa0465086db8e5a1e041f81,
title = "Controller parameters optimization of large inertia and time-varying load system based on extremum seeking algorithm",
abstract = "It is difficult to tune controller parameters for large inertia and time-varying load system. To solve this problem, a new controller parameters optimization strategy based on extremum seeking algorithm is proposed. This novel method is model-free. It utilizes data of experiments to get the gradient information of performance to control parameters, so as to tune the controller parameters. This paper analyzes the convergence of extremum seeking algorithm and proposes the high-pass filter parameters selection principles. Simulation and experimental results show that the system control performance is significantly improved using extremum seeking algorithm compared to traditional methods.",
keywords = "Extremum seeking, Gradient information, Large inertia system, Parameters tuning",
author = "Jiangbo Zhao and Feng Wei",
note = "Publisher Copyright: {\textcopyright} 2013 IEEE.; 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013 ; Conference date: 20-12-2013 Through 22-12-2013",
year = "2013",
doi = "10.1109/MEC.2013.6885058",
language = "English",
series = "Proceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "107--111",
booktitle = "Proceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013",
address = "United States",
}