Journal
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 51, Issue 3, Pages 1904-1916Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2019.2907620
Keywords
Protocols; State estimation; Time-varying systems; Job shop scheduling; Symmetric matrices; Cost function; Full information estimation (FIE); recursive state estimation (RSE); round-Robin (RR) protocol; time-varying systems (TVSs); uniform boundedness
Funding
- National Natural Science Foundation of China [61703245, 61873148, 61490701, 61751307]
- Taishan Scholar Project of Shandong Province of China
- China Post-Doctoral Science Foundation [2018T110702]
- Qingdao Post-Doctoral Applied Research Project [2016117]
- Post-Doctoral Special Innovation Foundation of Shandong [201701015]
- Royal Society of the U.K.
- Australian Research Council [DP160103567]
- Alexander von Humboldt Foundation of Germany
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This study addresses the full information estimation (FIE) problem for discrete time-varying systems subject to the effects of a round-Robin (RR) protocol. A novel recursive FIE scheme is developed and sufficient conditions for ensuring estimation performance are obtained. The solution of the proposed FIE scheme is achieved by solving a minimization problem, aiming for online applications.
The full information estimation (FIE) problem is addressed for discrete time-varying systems (TVSs) subject to the effects of a round-Robin (RR) protocol. A shared communication network is adopted for data transmissions between sensor nodes and the state estimator. In order to avoid data collisions in signal transmission, only one sensor node could have access to the network and communicate with the state estimator per time instant. The so-called RR protocol, which is also known as the token ring protocol, is employed to orchestrate the access sequence of sensor nodes, under which the chosen sensor node communicating with the state estimator could be modeled by a periodic function. A novel recursive FIE scheme is developed by defining a modified cost function and using a so-called backward-propagation-constraints. The modified cost function represents a special global estimation performance. The solution of the proposed FIE scheme is achieved by solving a minimization problem. Then, the recursive manner of such a solution is studied for the purpose of online applications. For the purpose of ensuring the estimation performance, sufficient conditions are obtained to derive the upper bound of the norm of the state estimation error (SEE). Finally, two illustrative examples are proposed to demonstrate the effectiveness of the developed estimation algorithm.
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