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Modelling of Aircraft’s Dynamics Using Least Square Support Vector Machine Regression

  • Hari Om VermaEmail author
  • Naba Kumar Peyada
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 655)

Abstract

The system identification is a broad area of research in various fields of engineering. Among them, our concern is to identify the aircraft dynamics by means of the measured motion and control variables using a new approach which is based on the support vector machine (SVM) regression. Due to the computational complexity of SVM, it is suggested to adopt the advanced version of SVM i.e. least square support vector machine (LSSVM) to be used for system identification. LSSVM regression is a network-based approach which requires a user defined kernel function and a set of input-output data for its training before the prediction phase like a neural-network (NN) based procedure. In this paper, LSSVM regression has been used to identify the non-linear dynamics of aircraft using real flight data.

Keywords

System identification LSSVM regression Kernel function 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Aerospace DepartmentIIT KharagpurKharagpurIndia

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