Knowledge and Wavelet Analysis Techniques in System Identification

Professor Natalia N. Bakhtadze, V.A. Trapeznikov Institute of Control Sciences, Moscow, Russia


A system identification method using the imitation of analyst’s associative thinking is presented. The identification method using associative search approach for action on knowledge about control object are given. The methods for developing predictive models in control systems and decision-making support for nonlinear non-stationary objects are proposed. The methods are based on the associative search procedure as well as on wavelet analysis techniques. An issues of the stability of a model built by use of the associative search are considered, in the aspect of the spectrum analysis of the multi-scale wavelet expansion. The methods proposed allow to predict the approach of process variables to critical values. Application examples from oil refining and chemical industries, power engineering are adduced.