Modeling of lateral dynamics of a UAV using system identification approach

System identification of an Unmanned Aerial Vehicle (UAV) for its mathematical modeling is an important step towards the automation of aircraft. A reliable mathematical model is also required for simulator design, aircraft crash analysis, studying the effects of aircraft modifications, preflight testing, stress distribution analysis and fatigue life appraisal etc. In this research work flight experiment was conducted for identification of lateral dynamics of a fixed wing UAV. Aircraft states were recorded during specifically designed flight maneuvers. After necessary preprocessing and bias removal, acquired data was further processed in Matlab System Identification toolbox for estimating lateral dynamics transfer functions related to aileron and rudder inputs. The black box identification based transfer function models were estimated using least square error estimation technique. The identification results present a reliable lateral model of the UAV with high level of confidence and goodness of fit between the actual system response and estimated model. The identified transfer function models can be used for various applications including heading controller design for an autopilot.