Author:
Sara Mohan George ,S. S. Selvi ,J. R. Raol
Abstract
The use of Gaussian Sum Filter (GSF) as a state/parameter estimation tool for aerodynamic modelling is relatively unexplored in the literature. In this paper GSF has been employed for aircraft parameter estimation. The stability analysis of GSF has also been discussed using the normalized Lyapunov energy functional and the conditions for the convergence of the GSF are derived by using the proposed nonlinear observer which is a novel approach. An approach to prune the weights of GSF based on Pearson coefficient is considered. The performances of the three recursive parameter estimation algorithms: Extended Kalman Filter (EKF), the simplified version of the GSF and the improved version of the GSF are evaluated for aircraft parameter estimation using simulated flight data in the MATLAB implementations. The numerical results show that pruning the weights reduces the computational load by nearly 75%, and still provides good performance compared to the conventional GSF.
Reference23 articles.
1. Raol, J. R. and J. Singh., "Flight Mechanics Modelling and Analysis", CRC Press, Taylor and Francis, Florida, USA, 2010.
2. Raol, J. R., Girija, G. and J. Singh., "Modelling and Parameter Estimation of Dynamic Systems", The IEE/IET Control Series Vol.65, London, 2004.
3. Chauhan, K. and Singh, S., "Review of Aerodynamic Parameter Estimation Techniques", International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), Dubai, pp.864-869, 2017.
4. Chen, R. T. N., Eulrich, B. J. and Lebacqz, J. V., "Development of Advanced Techniques for the Identification of V/STOL Aircraft Stability and Control Parameters", Cornell Aeronautical Lab., Inc., USA, Report No. BM-2820-F-1, 1971.
5. Majeed, M. and Narayan Kar, I., Aerodynamic Parameter Estimation Using Adaptive Unscented Kalman Filter", Aircraft Engineering and Aerospace Technology, Vol.85 No.4, pp.267-279, 2013.