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Distributed unknown input observers for interconnected nonlinear systems

Nonlinear interconnected systems such as complex biological processes and power networks operate using local state information. This is because global network states are generally unavailable, arrive with time-delays, or require expensive infrastructure. Coupled with nonlinear interconnections, state disturbances, and sensor noise/attacks, distributed state estimation is an extremely challenging problem. In this paper, distributed unknown input observers are proposed for estimating the internal states of the nonlinear subsystems using local measurement outputs. For each subsystem, the network configuration is exploited to formulate sufficient conditions for the estimation of the unknown input to arbitrary accuracy. The effectiveness of the proposed method is illustrated on the synthetic repressilator network in Escherichia coli.