Event-based recursive filtering for a class of nonlinear stochastic parameter systems over fading channels

Abstract

In this paper, the recursive filtering problem is studied for a class of time-varying nonlinear systems with stochastic parameter matrices. The measurement transmission between the sensor and the filter is conducted through a fading channel characterized by the Rice fading model. An event-based transmission mechanism is adopted to decide whether the sensor measurement should be transmitted to the filter. A recursive filter is designed such that, in the simultaneous presence of the stochastic parameter matrices and fading channels, the filtering error covariance is guaranteed to have an upper bound and such an upper bound is then minimized by appropriately choosing filter gain matrix. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed filtering scheme.

Keywords:

• Recursive filtering
• event-based transmission mechanism
• fading channels
• stochastic parameter matrices

Notes

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 61473076], [grant number 61525305], [grant number 61673103]; and the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning of China, and the Fundamental Research Funds for theh Central Universities [grant number CUSF-DH-D-2018091].