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Aircraft Aerodynamic Parameter Estimation Using Intelligent Estimation Algorithms
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Author(s): Abhishek Ghosh Roy (IIT Kharagpur, India) and Naba Kumar Peyada (IIT Kharagpur, India)
Copyright: 2019
Pages: 13
Source title:
Nature-Inspired Algorithms for Big Data Frameworks
Source Author(s)/Editor(s): Hema Banati (Dyal Singh College, India), Shikha Mehta (Jaypee Institute of Information Technology, India) and Parmeet Kaur (Jaypee Institute of Information Technology, India)
DOI: 10.4018/978-1-5225-5852-1.ch011
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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.
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