The problem of the synthesis of a tracking system for electromechanical control objects is considered when measuring only the generalized coordinates of the mechanical subsystem. It is assumed that external and parametric perturbations act on the system. Assuming the smoothness of external perturbations and uncertainties, the mathematical model of the control object is presented in the form of a joint block form of controllability and observability relative to the coordinate basis of mixed variables (functions of state variables, external influences, and their derivatives). Based on these conditions of the joint block form of parametric uncertainty of the matrix before the control actions, a procedure for decomposition synthesis of the basic law of discontinuous control has been developed. The basic control law ensures exponential convergence of the generalized coordinates to the reference signals. To obtain estimates of the mixed variables used in the feedback, a method for synthesizing an observer of a lower order state with large coefficients is proposed, in which the principle of complete decomposition is implemented. The results of numerical modeling of the developed algorithms for a three-link manipulator operating in a cylindrical workspace under incomplete information conditions are presented.

Different forms of control problems for linear systems under essential uncertainty are considered. Specifically, three problems are examined. First, the unknown disturbances are assumed bounded and only their bounds are known. The problem is solved under various assumptions regarding the order of the disturbances and the observed signals, as well as the properties of the system. Second, the estimation of the unknown input (i.e., the inversion problem or the inverse problem) is considered. This problem is solved by the controlled model method with the control designed to stabilize the difference between the observed outputs of the original system and the model. Robust stabilization algorithms produce estimates of the unknown signals with a desired accuracy. The third problem focuses on stabilization of switched systems. The dynamics of the chosen system is described at each instant by one of the systems from a given finite set. Switching between regimes may depend both on time and on the system phase vector. Two problems are solved successively: finding stabilizers (a unique stabilizer if possible) for each plant from the family, and then investigating the conditions when switching between stable regimes does not disrupt the stability of the switched system. Various stabilization methods are obtained for switched systems covering different switching schemes.

We solve the output controller synthesis problem for multidimensional systems, guaranteeing the following parameters, either predefined or achievable: control errors, stability margin radius, and control time under the action of polyharmonic external disturbances with unknown amplitudes (with a limit on their sum), frequencies, and an unbounded number of harmonics. Our approach to solving the problem is based on a specially designed standard H-inf-optimization problem and a new rule for choosing a weight matrix for a given accuracy. For the first time, we give a physical interpretation of the stability margin radius of multidimensional systems in terms of Nyquist hodographs for individual contours that are open at the output of the object. We prove a connection between the absolute stability property of a closed system and the radius of stability margin. We consider the example of synthesis for an interconnected electric drive.

Значительное повышение технических возможностей беспилотных летательных аппаратов (БПЛА) создает условия для расширения их использования в областях, где возможности человека ограничены. Такие приложения, как мониторинг объектов в труднодоступных местах, экстремальные спортивные ралли, спасательная операция, требуется наблюдение за объектами в крупных регионах и сложных условиях. Для обеспечения высокого уровня автономности БПЛА, необходимо решить три основные задачи: интеллектуальное планирование миссий, распознавание объектов в полете, модификация маршрутов полета в соответствии с меняющимися условиями. В статье представлены алгоритмы для решения этих задач на основе методов искусственного интеллекта.

This paper presents a matrix inequality approach to sensor fault estimation in presence of random input disturbance with unknown covariance. The input is supposed to be a correlated stationary Gaussian noise with bounded mean anisotropy. The quality criterion is defined as anisotropic norm of the system. Anisotropic norm of the system defines gain from input disturbance with bounded mean anisotropy to output. The main contribution of the paper is sensor fault estimator design that allows to estimate sensor fault with guaranteed anisotropybased disturbance attenuation level. Numerical example is given.