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Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV)and its control is one of the recent research topics related to the field ofautonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wingNatureinspired (NI) FW MAV is modeled and controlled inspiring by its advancedfeatures like quick flight, vertical take-off and landing, hovering, and fastturn, and enhanced manoeuvrability when contrasted with comparable-sized fixedand rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilizedto demonstrate the NIFW MAV model, which has points of interest over firstprinciple based modelling since it does not depend on the system dynamics,rather based on data and can incorporate various uncertainties like sensorerror. The same clustering strategy is used to develop an adaptive fuzzycontroller. The controller is then utilized to control the altitude of the NIFWMAV, that can adapt with environmental disturbances by tuning the antecedentand consequent parameters of the fuzzy system.

Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle