Lateral aircraft parameter estimation using neuro-fuzzy and genetic algorithm based method
| Autor: | N. K. Peyada, Abhishek Ghosh Roy |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
020301 aerospace & aeronautics
0209 industrial biotechnology Adaptive neuro fuzzy inference system Engineering Neuro-fuzzy business.industry Estimation theory System identification Stability (learning theory) 02 engineering and technology Stability derivatives 020901 industrial engineering & automation 0203 mechanical engineering Control theory Generalized forces Genetic algorithm business |
| Zdroj: | 2017 IEEE Aerospace Conference. |
| DOI: | 10.1109/aero.2017.7943677 |
| Popis: | Application of adaptive neuro fuzzy inference system (ANFIS) based genetic algorithm (GA) optimization to the problem of aerodynamic modeling and parameter estimation for aircraft is addressed. A neuro fuzzy based GA optimizer capable of predicting generalized force and moment coefficients employing measured motion and control variables only, without the requirement of conventional variables or their time derivatives, is proposed. Furthermore, it is shown that such a model can be used to extract equivalent stability and control derivatives of a rigid aircraft. Results are presented for aircraft to showcase the applicability of the proposed algorithm for both modeling and estimation of lateral parameters. |
| Databáze: | OpenAIRE |
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