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We study a control problem under the conditions of inaccurate measurement of part of the state coordinates of a system of linear ordinary differential equations. The essence of the problem is to construct an algorithm for generating a feedback control ensuring that the trajectory of a given system traces the trajectory of another system subject to the influence of an unknown disturbance that is a function of time with square integrable Euclidean norm. The cases of both time-continuous and sampled measurements are considered. We indicate a set of algorithms for solving the problem that are robust under information interference and computational errors and are based on the constructions of guaranteed control theory. Each of the algorithms is focused on its own information conditions regarding the dynamics of the system and the measured coordinates. [ABSTRACT FROM AUTHOR]

The problem of reconstructing an unknown disturbance of a nonlinear system of ordinary differential equations from inexact measurements of some of the state coordinates is considered. A solution algorithm robust to noises is proposed that combines constructions of dynamic inversion and guaranteed control theories. The algorithm consists of two blocks: one dynamically reconstructs the unmeasured coordinates and the other reconstructs the disturbance. [ABSTRACT FROM AUTHOR]

The unknown input disturbance in a system of nonlinear ordinary differential equations is reconstructed from measurements of some of the state coordinates. A solution algorithm is proposed that is robust to information noises and computational errors. The algorithm is constructed using guaranteed control theory. [ABSTRACT FROM AUTHOR]

The dynamic reconstruction of input disturbances and unobserved state coordinates is considered. An algorithm based on the dynamic inversion theory is proposed, which is robust to observational and computational errors. [ABSTRACT FROM AUTHOR]

Discusses the reconstruction of input actions through measurements of a part of coordinates. Problem of robust reconstruction of variable inputs for a dynamical system by using results of inexact observations of its trajectory; Solution algorithms for a number of situations; Concepts of the theory of robust dynamic inversion; Statement of dynamic reconstruction problems.