Efficient solution for nonlinear dynamic estimation problem with model-reality differences

Kek, Sie Long and Tay, Kim Gaik and Chua, Kuan Chin (2014) Efficient solution for nonlinear dynamic estimation problem with model-reality differences. In: Proceedings of the International Conference on Mathematics, Statistics and Financial Mathematics 2014 with IASC-ARS Sessions (ICMSFM2014), 18-19 November 2014, Kuala Lumpur, Malaysia.

[img]
Preview
PDF
124Kb

Abstract

In this paper, a computational approach for solving the nonlinear dynamic estimation problem is proposed. Our aim is to estimate the nonlinear state dynamics. In our approach, the linear expectation model, which is added with the adjusted parameters, is introduced. On this basis, the differences between the original system and the model used can be measured repeatedly. Since the output is measureable from the original problem, it is fed back into the model, in turn, updates the estimation solution of the model used iteratively. As the convergence achieved, the model solution converges to the true solution of the original problem, in spite of model-reality differences. For illustration, an example is studied and the solution shows the efficiency of the approach proposed. Keywords: nonlinear dynamic estimation, iterative solution, model-reality differences, adjusted parameters, output measurement

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:nonlinear dynamic estimation; iterative solution; model-reality differences; adjusted parameters; output measurement
Subjects:Q Science > QA Mathematics > QA297 Numerical analysis. Analysis
Q Science > QA Mathematics > QA440 Geometry. Trigonometry. Topology
Divisions:Faculty of Science, Technology and Human Development > Department of Science and Mathematics
ID Code:6732
Deposited By:Mrs. Nurhayati Ali
Deposited On:29 Mar 2015 15:44
Last Modified:29 Mar 2015 15:44

Repository Staff Only: item control page