8Aerodynamic Derivative Calculation Using Radial Basis Function Neural Networks

Ranjan Ganguli

Department of Aerospace Engineering, Indian Institute of Science, Bengaluru, India

8.1 Introduction

Aerodynamic stability and control parameters or derivatives are widely used in real‐time simulation, handling qualities analysis and control system design. They play an important role in the development of robotic helicopter UAVs (Kendoul et al 2009; Mokhtari and Benallegue 2004; Mondrag et al 2010). Such helicopters are important for the monitoring of traffic, search and rescue operations, agricultural spraying, logistics and so on (Shakernia et al 1999a,b). Rotorcraft are important unmanned systems due to their capabilities of vertical and low‐speed flight. Several methods of aerodynamic derivative calculation for rotorcraft have been proposed (Agard 1991; Padfield 1999; Prouty 1986). The aerodynamic parameters calculated using the system identification based method are more accurate than those derived from other methods, such as analytical and numerical differentiation (Agard 1991; Padfield 1999). System identification involves reconstructing a simulation model structure and model parameters from experimental flight data. Typical system identification techniques range from simple curve fitting algorithms to complex statistical error analysis.

System identification has become a significant tool for applications such as model validation, handling qualities evaluation, control law design, ...

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