To Linearize Nonlinear System Model Using Sensitivity Functions

Abstract

This paper contains a new manner to simplifying nonlinear system models. The problem is to find a linear model so that the square error between the output of the nonlinear model and the output of the linear model is minimum for all considered time. To solve this problem, in the present paper, is suggested to use the potential capabilities of the parameter deviations and the sensitivity functions to compute the square error. Using sensitivity equations (models) with respect to the linearize parameters, it is possible, generally speaking, to obtain the sensitivity functions with respect to linearize parameters. Then, using a space-parameter diagram and an grapho-analytic method the parameters working point are funded. A particular application of the proposed solution is analyzed in later sections. It is about a mechanical well-known system. It is also suggested how this method can be combined with certain aspects of control design.