Probability-Guaranteed Envelope-Constrained Filtering for Nonlinear Systems Subject to Measurement Outliers

• 成果类型: Article
• 署名作者: Ma, Lifeng; Wang, Zidong; Hu, Jun; Han, Qing-Long
• 署名单位: Nanjing University of Science & Technology; Shandong University of Science & Technology; Brunel University; Harbin University of Science & Technology; Swinburne University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3016767
• 发表日期: 2021
• 页码: 3274-3281
• 关键词: H-infinity filtering; envelope-constraint in probability; finite-horizon filtering; measurement outliers; Nonlinear systems

摘要

This article deals with the recursive filtering problem for nonlinear time-varying stochastic systems subject to possible measurement outliers. In order to mitigate the effects from possible abnormal measurements, we construct a filter with a saturation constraint imposed on the innovations where the saturation level is adaptively determined according to the estimation errors. Two performance indices, namely, the finite-horizon H-infinity specification and the envelope-constraint criterion with a prescribed probability, are put forward to describe the transient characteristics of the filtering error dynamics over a specified time interval. The purpose of the addressed problem is to design a filter capable of guaranteeing both the finite-horizon H-infinity performance index and the probability-guaranteed envelope-constraint. Sufficient conditions are derived for the existence of the desired filter via certain convex optimization algorithms. Finally, an illustrative numerical example is proposed to demonstrate the effectiveness of the developed algorithm.