Title |
Data-Driven State Observer Design and Filtering Technique for The Angular Acceleration Estimation of Dynamic Systems |
Authors |
이상덕(Sang-Deok Lee) ; 정슬(Seul Jung) |
DOI |
http://doi.org/10.5370/KIEE.2019.68.2.342 |
Keywords |
Angular acceleration estimation ; Data-driven state observer ; Complementary filter |
Abstract |
In this paper, we propose a data-driven state observer design and a filtering technique for the estimation of the angular acceleration information of dynamic systems. Angular acceleration information is quite useful for the control of vehicles, mobile robots, and joint systems. When the accurate angular acceleration state is estimated, we can construct a joint independent control scheme neglecting the dynamically coupled effects between the joints or links. An angular acceleration state observer based on the data of the measurable encoder is designed. However, such a data-driven state observer may show the peaking effect when the data are not enough or when the sampling rates are not fast. A simple first-order complementary filter is proposed to deal with the peaking effect problem. The proposed method is verified by the simulation and experimental studies. |