期刊
JOURNAL OF VIBRATION AND CONTROL
卷 26, 期 5-6, 页码 306-317出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1077546319878985
关键词
Time-varying systems; output-only; recursive identification; gross errors; adaptive weighting strategy
资金
- National Natural Science Foundation of China [11802201, 51575378, 11972245]
- China Postdoctoral Science Foundation [2017M621075]
Gross errors are generally used to model intermittent sensor failures and occasional data packet losses or corruption, which arise in many engineering communities. In this work, we propose to deal with the problem of output-only recursive identification of time-varying systems subject to gross errors by using an adaptive weighting and forgetting combined strategy. Under the assumption that gross errors are unknown and can be of arbitrarily large magnitude, time-dependent autoregressive model-based adaptive recursive identification methods are proposed by minimizing the sum of norm errors and achieving a sparse prediction error sequence. The adaptive weighting strategy is used to deemphasize data observations contaminated by gross errors, and the forgetting mechanism is used to deemphasize data from the remote past, allowing the proposed methods to track time-varying dynamics of the system subject to gross errors. The proposed methods are numerically and experimentally tested, and the comparative results demonstrate the superior time-varying tracking capability of the proposed methods in extremely challenging gross error circumstances.
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