Fuzzy clustering based modelling and adaptive controlling of a flapping wing micro air vehicle

Development of Flapping Wing Micro Air Vehicle (FW MAV) is one of the latest research topics related to the field of autonomous Unmanned Aerial Vehicles (UAVs). A four wing Bio-inspired (BI) FW MAV is selected in this work due to advantages which include fast flight, vertical take-off and landing, hovering, and quick turn, and enhanced manoeuvrability when compared to similar sized fixed and rotary wing UAVs. The Fuzzy C-Means clustering algorithm is utilized to model the BIFW MAV, which has advantages over first principle based modelling since it does not need any information about the system dynamics and can incorporate various uncertainties like sensor error. The same fuzzy clustering technique is utilized to control the altitude of the BIFW MAV, which can adapt with various environmental perturbations by changing the centre and width of the Gaussian membership function.