Aircraft Aerodynamic Parameter Estimation Using Intelligent Estimation Algorithms

Abstract

Application of adaptive neuro fuzzy inference system (ANFIS)-based particle swarm optimization (PSO) algorithm to the problem of aerodynamic modeling and optimal parameter estimation for aircraft has been addressed in this chapter. The ANFIS-based PSO optimizer constitutes the aircraft model in restricted sense capable of predicting generalized force and moment coefficients employing measured motion and control variables only, without formal requirement of conventional variables or their time derivatives. It has been shown that such an approximate model can be used to extract equivalent stability and control derivatives of a rigid aircraft.

Estimation of aerodynamic parameters using neural artificial bee colony fusion algorithm for moderate angle of attack using real flight data

“…ANN easily handles the non-linearity compared to the older statistical approaches, thereby gaining a universal approximator status. [24][25][26] ANN works with nonparametric models, whereas most statistical methods are based on parametric models, requiring a solid understanding of statistical data. With the Back Propagation (BP) learning approach, ANN effectively addresses the lacuna of traditional classification and forecasting methods.…”