in this paper, a new algorithm for system identification based on frequency response is presented. in this method, given a set of magnitudes and phases of the system transfer function in a set of discrete frequencies, a system of linear equations is derived which has a unique and exact solution for the coefficients of the transfer function provided that the data is noise-free and the degrees of...

When performing nonlinear system identification few tools exist for the a priori nonlinear model structure selection of the nonlinear system. This paper presents a possible approach as a first step towards selecting a nonlineAtr system model structure, based on using the results of Lyapunov exponents, Poincar~ maps and dimension techniques. The approach is illusUated by applying it to the Chua ...

The identification accuracy of dynamic characteristics coefficients is difficult to guarantee because of the errors of the measurement system itself. A novel dynamic calibration method of measurement system for dynamic characteristics coefficients is proposed in this paper to eliminate the errors of the measurement system itself. Compared with the calibration method of suspension quality, this ...

The long term goal attaining of economic system management requires the establishment of a dynamic framework to integrate multiple perspectives. This article considers the problem of economic development in macro level. As economic systems are complex adaptive systems composed of numerous numbers of components of dynamic and multidimensional nature, dynamics method is applied in this research. ...

This paper presents a frequency domain identification of dynamic model parameters for frictional presliding behavior. The identification procedure for the dynamic model parameters, i.e., 1) the stiffness and 2) the damping of the presliding phenomenon, is reduced from performing several dedicated experiments to one experiment where the system is excited with random noise and the frequency respo...

Different models can be used for nonlinear dynamic systems identification and the Gaussian process model is a relatively new option with several interesting features: model predictions contain the measure of confidence, the model has a small number of training parameters and facilitated structure determination, and different possibilities of including prior knowledge exist. In this paper the fr...

in the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. in this study, hydrodynamic coefficients of an autonomous un...

Genetic programming can be used to evolve an algebraic expression as part of an equation representing measured input-output response data. Parts of the nonlinear differential equations describing a dynamic system are identified along with their numerical parameters using genetic programming. The results of several such optimisations are analysed to produce a nonlinear physical representation of...

The analysis of input design for parameter estimation the linear, dynamic Single Input Output (SISO) second order systems is focus this paper. open loop system identification method considered different signals in work. Numerical algorithm Subspace State Space System Identification (N4SID) used identification. In work, five are Amplitude Pseudo Random Binary Sequence (APRBS) and Multisine given...

The class of nonlinear dynamic systems which can be represented by the block-oriented models, ie, by interconnection of linear dynamic and nonlinear static subsystems, has been studied by many authors. In the simplest case the models consist of a combination of two blocks giving the so-called Hammerstein (nonlinear-linear) and Wiener (linear-nonlinear) models and there are many methods for nonl...