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Recursive Filtering for Multi-Rate Nonlinear Systems With Unknown Inputs Based on Hybrid Event-Triggered Mechanisms
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胡
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DOI：10.1002/acs.70123.png)
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Abstract
En 中文
In this paper, the recursive filtering algorithm design problem is investigated for multi-rate nonlinear systems subject to unknown inputs under a hybrid event-triggered mechanism (HETM). To address the multi-rate sampling issue, the considered system is converted into an equivalent single-rate formulation by iterating the system state equation. Additionally, for the sake of conserving communication resources, the HETM, which integrates time-triggered and event-triggered mechanisms, is employed to schedule data transmission from the sensor to the filter over the network. The focus is on the development of a novel hybrid event-triggered recursive filtering strategy that simultaneously accounts for unknown inputs and multi-rate sampling. Specifically, the upper bounds are firstly derived for both the filtering error covariance and the unknown input error covariance by utilizing matrix theory, and then the minimization of these upper bounds is achieved by designing appropriate filter gain matrices. Finally, the feasibility and validity of proposed recursive filtering scheme are demonstrated through a simulation experiment.
Keywords:
hybrid event-triggered mechanism
minimization evaluation
multi-rate nonlinear systems
recursive filtering
unknown inputs
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