Bayesian Filters for Parameter Identification of Duffing Oscillator. Issue 1 (2018)

• Record Type: Journal Article
• Authors: Mishra, Vikas Kumar; Radhakrishnan, Rahul; Singh, Abhinoy Kumar; Bhaumik, Shovan
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 1(2018)
• Page Start: 425
• Page End: 430
• Publication Date: 2018
• Subjects: Nonlinear filtering -- Duffing oscillator -- Third-degree spherical cubature rule -- Higher order Gauss-Laguerre quadrature rule -- multidimensional Gauss-Hermite quadrature rule; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.05.068
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In this paper, a joint state and parameter estimation problem of Duffing oscillator is explored using Bayesian filters, where the parameter to be identified is considered as an additional state variable. From a variety of Bayesian filters, the unscented Kalman filter (UKF), cubature Kalman filter (CKF) and Gauss-Hermite filter (GHF) are chosen for solving this problem. The performance of these filters are compared in terms of the root mean square error (RMSE) calculated over a specified number of Monte-Carlo runs. From simulation results, it is found that the accuracy of CKF and GHF are almost same while the computational time for GHF is almost three times higher.