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- W2904073911 abstract "Detectability is the key property which underlies the design of any convergent observer. In this paper a method for analyzing the detectability for a class of networks of systems with unknown inputs is presented, exploiting the definition of indistinguishable trajectories and the structure of the underlying network graph. This analysis yields sufficient conditions for the sensor location in order to ensure the system’s strong detectability in presence of unknown inputs. Based on this analysis a simple (reduced order) unknown-input observer with explicit convergence conditions in terms of system parameters and the sensor locations is proposed and tested in numerical simulations for an illustrative case example of a Markov-chain based epidemic spreading model in a scale-free network with N = 103 nodes." @default.
- W2904073911 created "2018-12-22" @default.
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- W2904073911 date "2018-01-01" @default.
- W2904073911 modified "2023-10-14" @default.
- W2904073911 title "Strong detectability and unknown input observer design for a class of networks of systems" @default.
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- W2904073911 doi "https://doi.org/10.1016/j.ifacol.2018.12.009" @default.
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