Title：Remote State Estimation Under Compression-Decompression Mechanism

Abstract：In this presentation, we talk about the remote state estimation for nonlinear systems under a compression-decompression mechanism (CDM). Considering the redundancy embedded in the measurements, compressive sensing is utilized for high-performance CDM and the combined impact of measurement noise and quantization errors on decompression errors is analyzed. A modified unscented Kalman filter is devised to minimize an upper bound of the estimation error covariance. Simulation experiments are conducted based on the IEEE 69 bus system. Finally, we conclude our main contributions and some future directions.

Speaker：Wang Zidong，Brunel University London.

Date：10:00 a.m., 2024-7-23 (Tuesday).

Venue: Room 208, School of Mathematical Science

Organizer：School of Mathematical Science

Students and teachers are welcome.