Cooperative state and fault estimation of formation flight of satellites in deep space subject to unreliable information

S. M. Azizi, K. Khorasani

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


In this paper, a novel distributed cooperative estimation framework for a formation flight of satellites is proposed. This framework is developed based on the notion of sub-observers. Within a group of sub-observers each one is estimating certain states that are conditioned on a given input, output, and state information. In order to guarantee the ultimate boundedness of the estimation errors, a sub-observer dependency (SOD) digraph is introduced that is assumed to be acyclic. The overall estimation process is modeled by a weighted sub-observer dependency estimation (WSODE) digraph. By selecting an optimal path in the WSODE digraph, a high-level supervisor can then select and configure a set of sub-observers to successfully estimate all the system states. In presence of unreliable information due to large disturbances, noise, and actuator faults certain sub-observers may become invalid. In this case, the supervisor reconfigures the set of sub-observers by selecting a new path in the WSODE digraph such that the impacts of these uncertainties are managed and confined to only the local estimates of states and faults. This will consequently prevent the propagation of uncertainties to the entire estimation process and the performance degradations to the entire formation flight of satellites. Simulations are conducted for a five satellite formation flight system in deep space and the comparative results with a centralized Kalman filter (CKF) technique are shown to confirm the validity and advantages of our developed analytical work.

Original languageEnglish (US)
Pages (from-to)206-213
Number of pages8
Issue number12
StatePublished - Oct 2019
Externally publishedYes
Event21st IFAC Symposium on Automatic Control in Aerospace, ACA 2019 - Cranfield, United Kingdom
Duration: Aug 27 2019Aug 30 2019

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering


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