Intelligence Of Control System Research Articles

Online Identification of Synchronous Generator Electromechanical Parameters for Intelligent Control Problems

The control system intelligence is determined by the ability to adapt to changing circuit-mode parameters. This approach is especially relevant for emergency automation, because the emer-gency depends on the huge number of factors. In addition, an accident can develop in cascade, causing uncontrolled and multiple changes in the grid topology and mode parameters. The for-mation of the control actions volume of emergency automatics is carried out on the basis of the computing of the mode on mathematical models of electrical grids, the accuracy of which de-termines the adequacy of the actions of automation, so the models verifying problem arises, in-cluding electromechanical parameters determining of the grid elements. The aim of the research is to develop methods for parameter identification of synchronous generators. The paper pre-sents two methods for identifying the synchronous generator constant inertia and the method for identifying the synchronous inductive resistance. The research of the proposed methods was carried out on the digital model assembled in MatLab Simulink, where the 200 MVA 13.8 kV generator was simulated. In addition, the research was performed using the physical electrody-namic model. The parameters of the generator 3000 VA 230 V were determined. The results of parameters determining by the classical methods of open-circuit and short-circuit are presented. The significance of these methods is that the generator is connected to the grid and is in an op-eration mode. This will make possible to form and refine the model online in accordance with the circuit-mode situation, which will increase the control actions adequacy.

Training a New Generation of Engineers for Digital Economy

The domestic engineering industry is going through the stage of system introduction of digital technologies. The purpose of article is to present an experience of the department in the formation of the competences of a future engineer demanded in digital mechanical engineering. The department implements training methods corresponding to basic elements of a national technological initiative matrix such as digital modeling, mechatronics, additive technologies, artificial intelligence in control systems. Students master digital modeling in the end-to-end course of 3D modeling when dealing with design tasks of increasing complexity requiring the synthesis of independent, creative and competitive activities of students. Mechatronic modules are studied and designed in the educational process as the engineering competences demanded by employers. Additive technologies are studied at a laboratory of fast prototyping; the method of training combines team creation of electronic models, receiving a prototype of a product, and presentation of a result at student’s professionally focused competitions. Systems of artificial intelligence define the content of research work in interaction “student – teacher”. The new types of career-guidance work such as popular scientific lectures, excursions and practical work on the hi-tech equipment are highlighted. The authors also dwell on the prospects of training a new generation of mechanics in the conditions of the coming digital economy: the introduction of high-tech teaching aids, the implementation of the experience of immersive environments, gamification of training, the development of competences providing comprehensive skills for servicing virtual production corporations and intelligent devices.

Application of artificial intelligence in control systems of economic activity

The implementation of the tasks of evaluating historical financial information, the control or audit of business activities are based primarily on professional judgments about the object of study of a professional accountant or auditor. Their findings are drawn on the review of documents, the use of audit evidence, risk assessment, etc. There is always a probability (and rather high) that professional judgment will be based on incomplete information (since the dynamics of information changes is extremely high today), on the misstatements (since it is impossible to trace all the changes in knowledge related to the object of study), regardless of the quality of the performance of these individuals. In addition, the auditor often takes subjective decisions (for example, when choosing individual elements for the assessment from the general population), which also affects the degree of objectivity of his assessments. Artificial intelligence is the tool that could handle the entire set of knowledge, track all changes in the significant and important information, as well as in the insignificant and unimportant (which, however, also has an effect on the object of analysis). It does not have a work schedule or other restrictions on the time of work, so the comparison and analysis of information can be carried out around the clock, and the speed of data processing is determined by the processing power of the information systems, on which it operates, and is stably high. In this case, the artificial intelligence is ready to perform the tasks non-stop in real time till receiving the command of the termination of the process. This article proposes a methodology for the artificial intelligence use in the control systems of economic activity, reflects the artificial intelligence concept in the control systems of economic activity, indicates the goals, principles, tasks and its functions when checking an object.

Sertain Problematic Aspects of Fuzzy PID Regulation

In recent years in view of the fact that the interest in the technologies of artificial intelligence in control systems by technical objects and technological processes are aroused, that fuzzy controllers find use more often. The given regulators carry out the process of the development of controlling actions on the basis of fuzzy logic, the application of which provides the design of control systems capable of functioning in conditions of incompleteness and fuzziness of knowledge about the dynamics of the control object. Fuzzy regulators have opened a new direction in the area of automatic control and according to many experts have a promising future. The given paper analyzes the dynamic characteristics and algorithmic singularities of fuzzy PID-regulation systems, compares the quality of clear and fuzzy regulation. The conducted analysis allows to state the absence of any real advantages of fuzzy regulators in comparison with classic clear regulators. Moreover, it is possible to distinguish a number of problematic aspects of fuzzy regulation methodology, important for practical automation:fuzzy control algorithms are much more complex than traditional clear regulation algorithms;the thesis about the advantages of fuzzy regulators seems to be reasonable, since each such regulator can be replaced by a more efficient and structurally less complex clear regulator;the thesis that on the basis of fuzzy approach it is possible to synthesize working systems of regulation without a priori knowledge and pre-project inspection of dynamic properties of objects of regulation is disputable.fuzzy approach is purely empirical and does not allow to solve the problems of stability, dynamic quality and robustness of the synthesized regulation systems at the theoretical level;fuzzy control algorithms are not applicable to complex dynamic objects. In particular, it concerns multi-connected objects of regulation and objects with delay;the methodology of fuzzy regulation does not allow to solve the important issues of optimization of regulation processes for engineering practice.

II International Conference “Cognitive Robotics”

1. This issue of the journal is dedicated to the scientific and applied research presented at the II International Conference ʺCognitive Roboticsʺ. The conference was held on November 22–25, 2017 in Tomsk (Russia).The conference is organized by:The Russian Foundation for Basic Research.National Research Tomsk State University. Tomsk, Russia.National Research Tomsk Polytechnic University. Tomsk, Russia.JSC Scientific-Research Institute of Semiconductor Devices, Tomsk; Russia.Polzunov Altai State Technical University; Barnaul, Russia.Karaganda State Technical University, Karaganda, Kazakhstan.Information Satellite Systems named after Academician MF Reshetnev.Association of Innovative Enterprises and Organizations of Tomsk and Tomsk Region.“Radio-wave imaging” JSC. Tomsk, Russia.Anhalt University of Applied Sciences, Germany.Sponsors: National Instruments Corporation (USA).CONFERENCE SECTIONS: 1. Cognitive technologies and artificial intelligence in control systems for land and air-based robotic systems, and robotic submarines. 2. Sensing technology for land and air-based robotic systems, and robotic submarines. 3. Design of robotic systems (UAVs, AUVs). 4. Psycho-emotional and socio-humanitarian aspects of robotics. 5. Educational robotics2. CommitteeConference chairman: Vladimir I. Syryamkin, D.Eng.Sc., professor, Head of the Department of Quality Control of the Faculty of Innovative Technologies, National Research Tomsk State University; academician of International Academy of Sciences of Higher Education and Russian Academy of Natural Sciences; Director of TSU scientific and educational center «Recognition: navigation, diagnostics, mechatronics».Conference co-chairman - Eduard V. Galazhinsky, Doctor of Science (Psychology), Professor, academician of the Russian Academy of Education, Rector of Tomsk State University, Professor.Conference co-chairman – Stanislav V. Shidlovskiy - D.Eng.Sc., Dean of the Faculty of Innovative Technologies of National Research Tomsk State University; Head of the Laboratory of high-performance reconfigurable systems (NR TSU); Professor of Tomsk Polytechnic University.3. The Organizing Committee of the II International Conference ʺCognitive Roboticsʺ wishes to thank the IOP Conference Series Materials Science and Engineering-Team for collaboration.

ПЕРСПЕКТИВНЫЕ НАПРАВЛЕНИЯ УЛУЧШЕНИЯ ЭНЕРГОПТИМАЛЬНЫХ ПАРАМЕТРОВ И ТЯГОВЫХ СВОЙСТВ ЛОКОМОТИВОВ

Objective: To develop and justify energy-efficient and energy-saving control technology of traction electric drive with maximum realization of traction properties. Methods: Mathematical modeling, experimental manufacturing of prototypes of the converters and control system. Results: Theoretical justification was presented, based on refinement of the theory of energy processes in electrical circuits with solid state power controllers. It was proposed to apply electrical resistance of elements in electric power systems as a power control parameter instead of the conventional voltage. It was revealed that, in contrast to the existing analogues, semiconductor power regulators of different application with a new control parameter acquire the property of the electric variator. Technical solutions for manufacturing an innovative traction electric rolling stock were introduced with the use of advanced technical solutions of power control with adaptive control system that provides improved traction properties without shortening irreversible transformation of electric energy of power semiconductor devices. As an example, the solutions involving artificial intelligence in control systems of complex technical systems were presented, based on graphics processors, neural networks, providing parallel processing of large information arrays. Practical importance: Introduction of electric solid state variable speed with adaptive, intelligent control systems will significantly raise energy efficiency and improve the implementation of traction parameters of the locomotive.

Emerging Control Technologies: What Does the Future Hold?

There is increasing emphasis today on higher autonomy and intelligence in control systems that is driven by ever more demanding control requirements and fueled primarily by recent significant advances in sensor, actuator, computer and computer network technologies. Distributed control methodologies and coordination of interacting intelligent systems over networks will bring sophisticated control and decision methodologies where the needs are. We are at the dawn of a new era in control and decision systems which has the potential to significantly benefit agriculture. Highly demanding control requirements in production and processing of agricultural products coupled with the complexity and uncertainty of the models require the use of sophisticated control methods. Areas that stand to benefit from the use of advanced methods include the control and management of greenhouses, water resources, energy etc as well as all areas of processing and distributing agriCUltural products.