@inproceedings{4ff95edfb61f40729a63035538f8c3d3,
title = "Proportional-Integral Interval Observer for Linear Continuous-Time Systems",
abstract = "This work investigates H∞ proportional-integral interval observer for linear continuous-time systems via bounded disturbances. To reestablish system states with more dynamic information, three estimation approaches are provided by means of system outputs, namely, Luenberger type is given firstly without any prior constraints. Resorting to the framework of former, cooperativity is ensured by coordinate transformation in second approach. Lastly, extra parameters supplied by unknown input observer structure is utilized to contain all possible trajectories with less conservatism than second one. A structure separation technique is employed to overcome the nonlinearity induced by the third method. Sufficient conditions are provided in terms of linear matrix inequalities to satisfy prescribed H∞ requirement. Simulations studies confirm its validity.",
keywords = "Interval observer, Linear continuous-time systems, Linear matrix inequalities",
author = "Tu Zhang and Xingzheng Wu and Liwei Li and Mouquan Shen",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022 ; Conference date: 03-08-2022 Through 05-08-2022",
year = "2022",
doi = "10.1109/DDCLS55054.2022.9858408",
language = "英语",
series = "Proceedings of 2022 IEEE 11th Data Driven Control and Learning Systems Conference, DDCLS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1308--1313",
editor = "Mingxuan Sun and Zengqiang Chen",
booktitle = "Proceedings of 2022 IEEE 11th Data Driven Control and Learning Systems Conference, DDCLS 2022",
address = "美国",
}