Passive identification of multivariable stabilization system elements’ dynamics

Abstract

Increasing domestic automatic control systems competitiveness requires the design work intensification based on the implementation of modern information technologies. Such implementation necessary condition is based on the control object dynamic model's improvement and real operating perturbations characteristics estimates' development with the help of the latest identification methods design and usage. Objective - to create an algorithm for structural identifying the controller transfer functions matrix, the control object's system of ordinary differential equations and the perturbations spectral densities matrix. The algorithm initial data include stabilization system control signals and it's output signals obtained in standard operating conditions. Method - minimization of an identification errors weighted dispersions sum by the Wiener – Kolmogorov’s method. Equations that allow one to calculate matrices of the controller's transfer functions and of the perturbation’s spectral densities, as well as to find a control object's ordinary differential equations system that minimize the identification error’s variance have been found. Processing results of the stabilization system’s work simulation based on these equations proves their correctness and illustrates the methodology of applying the new identification algorithm. Application of the new identification algorithm is limited by the following conditions fulfillment: signals in the stabilization circuit belong to a set of centered stationary random processes; measurement noises operate at the controller input and are independent from perturbations, the sensors transfer matrix is known.