@inproceedings{e61d126236754c5698f3c7bca2e6bb90,
title = "Controller design by using simultaneous perturbation stochastic approximation with changeable sliding window",
abstract = "Many searching problems use simultaneous perturbation stochastic approximation (SPSA) method so as to get optimal parameters nowadays. This paper proposes a model free control (MFC) method based on SPSA with changeable sliding window. The controller here is founded based on an improved SPSA algorithm whose sampling window is updated according to the variation of the system. As a kind of MFC method, the key advantage of this approach is that it can complete the controller design task by using the input and output data of the system instead of establishing a complex model for it. In order to improve the efficiency of the control method, a changeable sliding window is used here to estimate the parameters. After that convergence analysis for the improved SPSA method is also provided in this paper. Simulation results for hypersonic vehicle tracking problem demonstrate that compare with traditional SPSA algorithm this improved method can significantly improve the feasibility and efficiency.",
keywords = "Changeable window, Hypersonic vehicle, Model free control, SPSA",
author = "Qing Lu and Jun Zhou",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
year = "2019",
doi = "10.1007/978-3-030-27535-8\_59",
language = "英语",
isbn = "9783030275341",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "665--676",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
}