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This paper proposes a novel Gap Reduced Minimum Error Robust Simultaneous(GRMERS) estimator for resource-constrained Nano Aerial Vehicle (NAV) thatenables a single estimator to provide simultaneous and robust estimation for agiven N unstable and uncertain NAV plant models. The estimated full statefeedback enables a stable flight for NAV. The GRMERS estimator is implementedutilizing a Minimum Error Robust Simultaneous (MERS) estimator and Gap Reducing(GR) compensators. The MERS estimator provides robust simultaneous estimationwith minimal largest worst-case estimation error even in the presence of abounded energy exogenous disturbance signal. The GR compensators reduce the gapbetween the graphs of N linear plant models to decrease the estimation errorgenerated by the MERS estimator. A sufficient condition for the existence of asimultaneous estimator is established using LMIs and robust estimation theory.Further, MERS estimator and GR compensator design are formulated as non-convextractable optimization problems and are solved using the population-basedgenetic algorithms. The performance of the GRMERS estimator consisting of MERSestimator and GR compensators from the population-based genetic algorithms isvalidated through simulation studies. The study results indicate that a singleGRMERS estimator can produce state estimates with reduced errors for all flightconditions. The results indicate that the single GRMERS estimator is robustthan the individually designed H inifinity filters.

Gap Reduced Minimum Error Robust Simultaneous Estimation For Unstable Nano Air Vehicle