Vol 55, No 4 (2016)

Differential repetitive processes arise in the analysis and design of iterative learning control algorithms. They belong to a class of mathematical models whose dynamic properties are defined by two independent variables, such as a time and a spatial coordinate, also known as 2D systems in the literature. Moreover, standard stability analysis methods cannot be applied to such processes. This paper develops a vector Lyapunov function-based approach to the exponential stability analysis of differential repetitive processes and applies the resulting conditions to develop linear matrix inequality based iterative learning control law design algorithms in the presence of model uncertainty.

Hypothesis, internal, and output paths of the airborne, seaborne, and ground-based objects in a complex informational environment (low probability of detection, uncertainty and incompleteness of coordinates, maneuvering and group objects) onboard an aircraft are discussed. All measurements of internal and external sources operating in survey, passive detection, and tracking modes are used for calculation. For external sources the composition of transmitted data is determined. In the partial measurement of the coordinates, a complex aircraft control system is formed, which increases the accuracy of the paths of such objects and puts the aircraft in the conditions of a rocket launch with the maximum range.

An approach that allows finding a set of robust statistic feedback controllers that ensure the given control accuracy for the controlled parameters in a multiconnected control system under bounded parametric and external perturbations of various classes is proposed. To describe the set of controllers of the given accuracy, the results of analytically solving the matrix equations based on matrix canonization and parametrization of the Lyapunov equation are used. The solvability conditions of the synthesis problem ensure the robustness and optimal suppression of the perturbations. They are homogeneously represented as linear matrix inequalities obtained based on the Lyapunov functions. A methodological example is given.

In processing foreign personal names and surnames, the task of finding how to represent the way they sound in Russian often arises. This is important, for example, for intellectual property and other property paperwork, for translations, and for creating news stories. Information is often not available about the language of representation of the personal name. Therefore, the problem of automated identification of the language by the structure of the name-and-surname group is actual. Another problem is the automation of rule creation processes for the transcription of personal names. This paper proposes an algorithmic approach to solve these problems using the methods of machine learning.

Tactical-level onboard intelligent systems support the crew’s decision-making concerning real-time targeting and determining the way of achieving real-time-assigned targets (tactical objectives). The classification and image of intelligent systems and their interactions with the crew and between each other, as well as knowledge of the replenishment procedures in the course of operation, are presented.

A new way to interconnect multispectral images by using the methods of diffusive morphology are presented for implementing improved vision systems in aviation. In contrast to the traditional morphological methods, in the presented approach, it is not necessary to segment in advance the image for describing its shape and it ensures strong resistance against noise and distortions. Procedures for two- and three-channel image interconnection are developed based on diffusive morphological filtration. How to use them by using the image pyramid is also presented. A promising prototype of an improved vision system is described. The interconnecting algorithms are processed experimentally by using the multispectral data collected during an aviation experiment by using the described prototype.

We consider methodical issues of improving the efficiency of monitoring the state of aircraft and aviation groups through concerted use of modern information technologies. We give a mathematical formulation of the problem and appropriate algorithms; and we formulate and solve partial problems of determining the optimal control period for operations and data transmission in hierarchically organized systems under nonstationary and subjective conditions that cannot be easily taken into account.

A method for the remote control of a space robot is proposed for the case of large delays in the transmission of control signals from the Earth to the local robot control system and in feedback signals. The method involves the use of the model of the space robot and its current environment with the simulation of gravity conditions at the ground control center. In this model environment, the operator should carry out the required actions by controlling the space robot model in the master-slave mode using an arm with six degrees of freedom capable of reflecting the interaction force of a model robot working tool with models of the objects of the environment. The arm movement trajectory and the law of time variation of the reflected interaction force vector are program-based for the local space robot control system and should be executed by it upon reception from the ground control center. The robot’s possible erroneous actions generated by the inevitable inaccuracy of the environment model are compensated by the proposed method of programmed trajectory correction. In accordance with it, in order to generate correction signals, additional information received from different sensors is used. These sensors can be installed on both the model and space robot itself. This information includes data on the mutual position of a robot’s working tool and models of the objects of the environment, as well as on the interaction forces between them. The paper presents a detailed theoretical justification of the proposed approach and experimental results that confirm the theoretical conclusions.