Visible to the public Analytical synthesis of reduced order observer for estimation of the bilinear dynamic system state

TitleAnalytical synthesis of reduced order observer for estimation of the bilinear dynamic system state
Publication TypeConference Paper
Year of Publication2017
AuthorsDem'yanov, D. N.
Conference Name2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
Date Publishedmay
Keywordsanalytical synthesis, bilinear dynamic system, bilinear dynamic system state estimation, bilinear systems, composability, control system synthesis, Dynamical Systems, estimation error, Heuristic algorithms, Industrial engineering, Kalman filters, Manufacturing, Mathematical model, matrix algebra, matrix canonization, matrix canonization technology, matrix coefficients, Metrics, Nonlinear dynamical systems, nonlinear observer, observer coefficients, observer dynamic equation, Observers, output signal, pubcrawl, reduced order observer, reduced order state observer, reduced order systems, resilience, Resiliency, scalar input, solvability, state observer, synthesis problem, vector output, Vectors
Abstract

The problem of analytical synthesis of the reduced order state observer for the bilinear dynamic system with scalar input and vector output has been considered. Formulas for calculation of the matrix coefficients of the nonlinear observer with estimation error asymptotically approaching zero have been obtained. Two modifications of observer dynamic equation have been proposed: the first one requires differentiation of an output signal and the second one does not. Based on the matrix canonization technology, the solvability conditions for the synthesis problem and analytical expressions for an acceptable set of solutions have been received. A precise step-by-step algorithm for calculating the observer coefficients has been offered. An example of the practical use of the developed algorithm has been given.

URLhttps://ieeexplore.ieee.org/document/8076146
DOI10.1109/ICIEAM.2017.8076146
Citation Keydemyanov_analytical_2017