Abstarct: A review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy systems of Ukraine and Kazakhstan,are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed.

Relationship shifts within complex system may cause transfers from norm to pre-crisis or to crisis. Bifurcation values of bifurcation parameters can be calculated by means of proposed mathematical method. Sustainable development of society assumes a reasonable balance between the activities, directed to an acceleration of economic growth, and efforts, directed to mitigate a negative impact of such activities on environment. This problem is of great importance in the sphere of agro-industrial production that is the most sensible pin zone in the system of reciprocal influence of economic and ecological interests of humanity. The functioning of complex systems is becoming unstable and characterizing by discontinuous changes in their behavior. The main objective of investigations is to strengthen the capacity in fields as impact of uncertainty caused by Global Change on transformation of security and sustainability of complex systems for which standard modeling methods and tools are inadequate.

Nowadays contemporary economic growth and increasing industrial needs demand robots to have a multifunctional properties such as a wide applicability, precision, wide workspace and simple robot-human interface. Modern, robot industry presents two types of robot architecture: serial and parallel, serial robots have a wide workspace, easy forward kinematics and have a wide applicability in industry, while parallel manipulators are not applies widely in industry. However, parallel manipulator has some beneficial properties as well, such as rigidity, high payload capacity and high precision. Although majority robots in industry are serial manipulators, but some areas of industry where requires high precision and rigidity utilizes parallel manipulators such as medicine, pharmacy and microchip assembling industry. The novelty of this project is creating of new type of robot combination: common serial manipulator with Delta robot. Furthermore, to investigate capabilities of this Hybrid robot in terms kinematics, dynamics, payload capacity and accuracy. Moreover, this research will explain serial/parallel hybrid manipulator design structure, workspace control system and kinematics of both manipulators as well.

High spatial resolution satellite images are different from Gaussian statistics of counts. Therefore, texture recognition methods based on variances become ineffective. The aim of this paper is to study possibilities of completely different, topological approach to problems of structures classification. Persistent Betti numbers are signs of texture recognition. They are not associated with metrics and received directly fromdata in form of so-called persistence diagram (PD). The different structures built on PD are used to get convenient numerical statistics. At the present time, three of such objects are known: topological landscapes, persistent images and rank functions. They have been introduced recently and appeared as an attempt to vectorize PD. Typically, each of the proposed structures was illustrated by the authors with simple examples.However, the practical application of these approaches to large data sets requires to evaluate their efficiency within the frame of the selected task at the same standard database. In our case, such a task is to recognize different textures of the Remote Sensing Data (RSD). We check efficiency of structure, called persistent images in this work. We calculate PD for base containing 800 images of high resolution representing 20 texture classes. We have found out that average efficiency of separate image recognition in the classes is 84%, and in 11 classes, it is not less than 90%. By comparison topological landscapes provide 68% for average efficiency, and only 3 classes of not less than 90%. Reached conclusions are of interest for new methods of texture recognition in RSD.

The solution of three-dimensional (3D) coordinate calculation task for a material point is considered. Two flat images (a stereopair) which correspond to the left and to the right viewpoints of a 3D scene are used for this purpose. The stereopair is obtained using two cameras with parallel optical axes. The analytical formulas for calculating 3D coordinates of a material point in the scene were obtained on the basis of analysis of the stereoscopic system optical and geometrical schemes. The detailed presentation of the algorithmic and hardware realization of the given method was discussed with the the practical. The practical module was recommended for the determination of the optical system unknown parameters. The series of experimental investigations were conducted for verification of theoretical results. During these experiments the minor inaccuracies were occurred by space distortions in the optical system and by it discrecity. While using the high quality stereoscopic system, the existing calculation inaccuracy enables to apply the given method for the wide range of practical tasks.