Work

Multi-Sensor Scheduling for State Estimation with Event-Based, Stochastic Triggers

Year: 2015

Type: preprint

Abstract: In networked systems, state estimation is hampered by communication limits. Past approaches, which consider scheduling sensors through deterministic event-triggers, reduce communication and maintain estimation quality. However, these approaches destroy the Gaussian property of the state, making it computationally intractable to obtain an exact minimum mean squared error estimate. We propose a stochastic event-triggered sensor schedule for state estimation which preserves the Gaussianity of the system, extending previous results from the single-sensor to the multi-sensor case.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1502.03068

Authors: Weerakkody, Sean, Mo, Yilin, Sinopoli, Bruno, Han, Duo, Shi, Ling

Institutions: Carnegie Mellon University, Nanyang Technological University, Hong Kong University of Science and Technology

Language: English

Topic: Stability and Control of Uncertain Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Awards: CPS: Medium: Collaborative Research: The CyberPhyscial Challenges of Transient Stability and Security in Power Grids, G6671297155, CAREER: Efficient, Secure and Robust Control of Cyber Physical Systems

OpenAlex ID: W2172297533

Cites: 11

Cited by: 1

Related to: 10