期刊
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷 51, 期 5, 页码 2937-2948出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2019.2918002
关键词
Estimation; Protocols; Artificial neural networks; Nonlinear systems; Scheduling; Automation; Symmetric matrices; Moving horizon (MH) estimation; networked systems (NSs); nonlinear systems; random access (RA) protocol; recursive estimator
资金
- National Natural Science Foundation of China [61873148, 61703245, 61490701, 61751307]
- Taishan Scholar Project of Shandong Province of China
- Australian Research Council [DP160103567]
- Alexander von Humboldt Foundation of Germany
- China Post-Doctoral Science Foundation [2018T110702]
- Post-Doctoral Special Innovation Foundation of Shandong [201701015]
- Royal Society of the United Kingdom
This paper focuses on the moving horizon estimation issue for a type of networked nonlinear systems with a random access protocol scheduling effects. A novel nonlinear MH estimation scheme is developed to cope with the state estimation task, and sufficient conditions are established to guarantee that the estimation error is exponentially ultimately bounded in mean square.
This paper is concerned with the moving horizon (MH) estimation issue for a type of networked nonlinear systems (NNSs) with the so-called random access (RA) protocol scheduling effects. To handle the signal transmissions between sensor nodes and the MH estimator, a constrained communication channel is employed whose channel constraints implies that at each time instant, only one sensor node is permitted to access the communication channel and then send its measurement data. The RA protocol, whose scheduling behavior is characterized by a discrete-time Markov chain (DTMC), is utilized to orchestrate the access sequence of sensor nodes. By extending the robust MH estimation method, a novel nonlinear MH estimation scheme and the corresponding approximate MH estimation scheme are developed to cope with the state estimation task. Subsequently, some sufficient conditions are established to guarantee that the estimation error is exponentially ultimately bounded in mean square. Based on that the main results are further specialized to linear systems with the RA protocol scheduling. Finally, two numerical examples and the corresponding figures are provided to verify the effectiveness/correctness of the developed MH estimation scheme and approximate MH estimation scheme.
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