Protocol-Based Unscented Kalman Filtering in the Presence of Stochastic Uncertainties

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Abstract
In this paper, the unscented Kalman filtering (UKF) problem is investigated for a class of general nonlinear systems with stochastic uncertainties under communication protocols. A modified unscented transformation is put forward to account for stochastic uncertainties caused by modeling errors. For preventing data collisions and mitigating communication burden, the round-robin protocol and the weighted try-once-discard protocol are, respectively, introduced to regulate the data transmission order from sensors to the filter. Then, by employing two kinds of data-holding strategies (i.e., zero-order holder and zero input) for those nodes without transmission privilege, two novel protocol-based measurement models are formulated. Subsequently, by resorting to the sigma point approximation method, two resource-saving UKF algorithms are developed, where the impact from the underlying protocols on the filter design is explicitly quantified. Finally, compared with the protocol-based extended Kalman filtering algorithms, a simulation example is presented to demonstrate the effectiveness of the proposed protocol-based UKF algorithms.
Funding Information
  • National Natural Science Foundation of China (61873148, 61873169, U1509205)
  • National Postdoctoral Program for Innovative Talents (BX20180202)
  • Zhejiang Provincial Natural Science Foundation of China (LR16F030003)
  • Alexander von Humboldt Foundation of Germany

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