Algorithms of adaptive identification of uncertain operated objects in dynamical models

Abstract

Regular algorithms of adaptive estimation of a condition of objects of management with uncertainty are given in models of dynamics and external indignations. Algorithms of estimation of a covariance matrix of noise of an object on the basis of methods of the solution of the nonlinear functional equations taking into account possible unsolvability of the linearized system with the person or badly caused matrix are developed. Algorithms of iterative joint estimation the covariance matrixes of noise of an object and hindrance of measurements on the basis of the updating process and a method of secants are offered. Algorithms of estimation of matrix coefficient of strengthening of the Kalman filter on the basis of a gradient projection method are developed. Estimation algorithms at the correlated noise of an object and hindrance of measurements on the basis of methods of the decision of confidants of the degenerate or badly caused stochastic systems of the linear algebraic equations are offered.