期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 86, 期 -, 页码 1-15出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2016.09.028
关键词
Vibrating cantilever; Moving horizon estimation; Extended Kalman filter; Parameter estimation; Real-time implementation; Embedded systems; Structural monitoring
资金
- People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme under REA (TEMPO) [607957]
- Slovak Research and Development Agency (APVV) [APVV-14-0399, APVV-0090-10]
- Scientific Grant Agency (VEGA) of the Ministry of Education, Science, Research and Sport of the Slovak Republic [1/0144/15]
- STU Grant scheme for the Support of Excellent Teams of Young Researchers
Vibrating structures may be subject to changes throughout their operating lifetime due to a range of environmental and technical factors. These variations can be considered as parameter changes in the dynamic model of the structure, while their online estimates can be utilized in adaptive control strategies, or in structural health monitoring. This paper implements the moving horizon estimation (MHE) algorithm on a low-cost embedded computing device that is jointly observing the dynamic states and parameter variations of an active cantilever beam in real time. The practical behavior of this algorithm has been investigated in various experimental scenarios. It has been found, that for the given field of application, moving horizon estimation converges faster than the extended Kalman filter; moreover, it handles atypical measurement noise, sensor errors or other extreme changes, reliably. Despite its improved performance, the experiments demonstrate that the disadvantage of solving the nonlinear optimization problem in MHE is that it naturally leads to an increase in computational effort.
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