Identification of non-linear systems using correlation analysis and pseudorandom inputs

Algorithms for the identification of open- and closed-loop non-linear systems composed of linear dynamic and static non-linear elements are developed. It is shown that correlation analysis based upon compound pseudorandom inputs provides estimates of the individual component subsystems. The selection of pseudorandom inputs is discussed and simulated examples are included.

[1]  J. F. Coales,et al.  An Introduction to the Analysis of Non-Linear Control Systems with Random Inputs , 1956 .

[2]  H. Smets.  Analysis and Synthesis of Nonlinear Systems , 1960 .

[3]  J. Douce,et al.  Frequency spectrum distortion of random signals in non-linear feedback systems , 1961 .

[4]  G. Zames.  Functional Analysis Applied to Nonlinear Feedback Systems , 1963 .

[5]  K. R. Godfrey,et al.  Pseudorandom signals for the dynamic analysis of multivariable systems , 1966 .

[6]  H. R. Simpson.  Statistical properties of a class of pseudorandom sequences , 1966 .

[7]  G. Peckham,et al.  A New Method for Minimising a Sum of Squares Without Calculating Gradients , 1970, Comput. J..

[8]  W. D. T. Davies,et al.  System identification for self-adaptive control , 1970 .

[9]  H. A. Barker,et al.  High-order autocorelation functions of pseudorandom signals based on m sequences , 1970 .

[10]  S. Narayanan.  Application of Volterra series to intermodulation distortion analysis of transistor feedback amplifiers , 1970 .

[11]  N. Ream.  Nonlinear identification using inverse-repeatm sequences , 1970 .

[12]  H. A. Barker,et al.  Effects of nonlinearities on the measurement of weighting functions by crosscorrelation using pseudorandom signals , 1973 .

[13]  A. Gardiner.  Identification of processes containing single-valued non-linearities† , 1973 .

[14]  B. Cooper,et al.  Identification of simple nonlinear systems , 1975 .

[15]  K. Shanmugam,et al.  Analysis and synthesis of a class of nonlinear systems , 1976 .