Aircraft parameter estimation using ELM network
| Autor: | N. K. Peyada, Hari Om Verma |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
020301 aerospace & aeronautics
021110 strategic defence & security studies Artificial neural network Computer science Estimation theory 0211 other engineering and technologies System identification Aerospace Engineering 02 engineering and technology Flight simulator Maxima and minima Aerodynamic force 0203 mechanical engineering Feedforward neural network Algorithm Extreme learning machine |
| Zdroj: | Aircraft Engineering and Aerospace Technology. 92:895-907 |
| ISSN: | 1748-8842 |
| DOI: | 10.1108/aeat-01-2019-0003 |
| Popis: | Purpose The purpose of this paper is to investigate the estimation methodology with a highly generalized cost-effective single hidden layer neural network. Design/methodology/approach The aerodynamic parameter estimation is a challenging research area of aircraft system identification, which finds various applications such as flight control law design and flight simulators. With the availability of the large database, the data-driven methods have gained attention, which is primarily based on the nonlinear function approximation using artificial neural networks. A novel single hidden layer feed-forward neural network (FFNN) known as extreme learning machine (ELM), which overcomes the issues such as learning rate, number of epochs, local minima, generalization performance and computational cost, as encountered in the conventional gradient learning-based FFNN has been used for the nonlinear modeling of the aerodynamic forces and moments. A mathematical formulation based on the partial differentiation is proposed to estimate the aerodynamic parameters. Findings The real flight data of longitudinal and lateral-directional motion have been considered to estimate their respective aerodynamic parameters using the proposed methodology. The efficacy of the estimates is verified with the results obtained through the conventional parameter estimation methods such as the equation-error method and filter-error method. Originality/value The present study is an outcome of the research conducted on ELM for the estimation of aerodynamic parameters from the real flight data. The proposed method is capable to estimate the parameters in the presence of noise. |
| Databáze: | OpenAIRE |
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