Aerodynamic Parameters Estimation Using Radial Basis Function Neural Partial Differentiation Method

  • Jitu Sanwale Aircraft Upgrade Research & Design Centre, Hindustan Aeronautics Limited, Nasik - 422 207
  • Dhan Jeet Singh Aircraft Upgrade Research & Design Centre, Hindustan Aeronautics Limited, Nasik - 422 207
Keywords: RBF Neural Network, EKF, k-means clustering, PDM, Aerodynamic parameter estimation

Abstract

Aerodynamic parameter estimation involves modelling of force and moment coefficients and computation of stability and control derivatives from recorded flight data. This problem is extensively studied in the past using classical approaches such as output error, filter error and equation error methods. An alternative approach to these model based methods is the machine learning such as artificial neural network. In this paper, radial basis function neural network (RBF NN) is used to model the lateral-directional force and moment coefficients. The RBF NN is trained using k-means clustering algorithm for finding the centers of radial basis function and extended Kalman filter for obtaining the weights in the output layer. Then, a new method is proposed to obtain the stability and control derivatives. The first order partial differentiation is performed analytically on the radial basis function neural network approximated output. The stability and control derivatives are computed at each training data point, thus reducing the post training time and computational efforts compared to hitherto delta method and its variants. The efficacy of the identified model and proposed neural derivative method is demonstrated using real time flight data of ATTAS aircraft. The results from the proposed approach compare well with those from the other.

Author Biographies

Jitu Sanwale, Aircraft Upgrade Research & Design Centre, Hindustan Aeronautics Limited, Nasik - 422 207
Mr Jitu Sanwale has obtained his BE (Electronics & Instrumentation) and MTech (Communication Systems) from SGSITS Indore and IIT Roorkee, in 2006 and 2008, respectively. Presently, he is working as Manager (Design) in Hindustan Aeronautics Limited, Nasik. His areas of interest include: System identification, flight controller, autopilot and navigation systems of fixed wing aircrafts.
Dhan Jeet Singh, Aircraft Upgrade Research & Design Centre, Hindustan Aeronautics Limited, Nasik - 422 207
Mr Dhan Jeet Singh has obtained his BE (Electronics & Communication Engineering) from B.I.E.T Jhansi, in 2005 and perusing MS (Research) in Control and Automation from Department of Electrical Engineering, IIT Kanpur. Presently, he is working as Sr. Manager (Design) in Aircraft Upgrade Research & Design Centre (AURDC) of Hindustan Aeronautics Limited, Nasik. He has research experience in flight control and navigation systems of fixed wing fighter aircrafts.
Published
2018-04-16
How to Cite
Sanwale, J., & Singh, D. J. (2018). Aerodynamic Parameters Estimation Using Radial Basis Function Neural Partial Differentiation Method. Defence Science Journal, 68(3), 241-250. https://doi.org/10.14429/dsj.68.11843
Section
Aeronautical Systems