Viktoriya Zaripova

Knowledge Bases of Physical Effects and Phenomena for Method of Energy-Informational Models by Means of Ontologies

A large number of design methods was developed as a part of the science of engineering design. Unfortunately different physical properties that are the basis of sensor operation principle are described through the physical and mathematical tools corresponding to each and any phenomena class. This impedes automation of the design process, increases the period of new sensor development and their cost. In recent years creation of vast knowledge bases and using ontologies for fast and relevant search became a trend in engineering design. The article proposes the complex of information processing methods based on ontologies to create a knowledge base of physical effects. Classification of various physical phenomena in the knowledge base is based on energyinformation model of circuits (EIMC) suggested by the authors.

System of Conceptual Design Based on Energy-Informational Model

A large number of design methods were developed as a part of the science of engineering design. In recent years creation of vast knowledge bases and using ontologies for fast and relevant search became a trend in engineering design. The article demonstrates that data base on physical phenomena and effects is the key component of the conceptual design methodology. In this article we present a System for Conceptual Design Based on Energy-Informational Model (EIM). We consider designing of the knowledge base on basis of knowledge about physical effects and domain ontology. In conclusion we provide a comparison of proposed methodology with known methods: the Theory of Inventive Problem-Solving (TRIZ) and the systematic approach of Pahl and Beitz (SAPB)

Ontological Knowledge Base of Physical and Technical Effects for Conceptual Design of Sensors

This article discusses design of the knowledge base of physical phenomena based on domain-specific ontology. Classification of various physical phenomena in the knowledge base is based on energy-information model of circuits (EIMC) suggested by the authors. This model is specially aimed at design of new operating principles of sensing elements (sensors). Such a knowledge base can be used to train intended engineers, specialists in sensors design.

Robust Adaptive Control of the Dynamic Multilinked Object: Control of Robot Manipulator

In article, the problem of the robust adaptive control of the dynamic multilinked object with local reference models is investigated. Exchange of information between local subsystems is thus forbidden and only scalar input and output signals are available to measurement, i.e. completely decentralized control is realized. As an example, the designed algorithm is used for control of the robot manipulator. Results of computer modeling of control of motion of the end of manipulator from one point to another are given. The article describes control of robot manipulator on the closed curve.

Modeling of the Physical Principle of the Processes that is Occurring in Bioselective Elements

Design of biosensors refers to the field of interdisciplinary research, therefore, it is necessary to develop a unified systems approach that is invariant to the physical nature of the used phenomena and processes to create an automated system for conceptual design of such elements. It is appropriate to choose the fundamentals of non-equilibrium thermodynamics as the basis for the development of this approach. This article discusses the energy-information model of diffusion phenomena, as the processes of diffusion is the general type of the processes that is occurring in bioselective elements. A number of physical effects are described by this model. In this paper authors continue researches in the field of automation of design of biosensors which was presented at the 6th International Conference on Information, Intelligence, Systems and Applications. The new information technology of functional and structural design of biosensors is described. It is based on the energy-information model of chains, invariant to the physical nature of the processes occurring in technical devices. And it uses the device parametric structural diagrams allowing algorithmization of the search and selection of new technical solutions with estimation of their performance.

System of Automated Design of Biosensors

The article considers the creation of two knowledge bases on physicotechnical effects and bioreceptors, which are planned to be used at the stage of conceptual design of biosensors. About 40 physical and technical phenomena are described, a class diagram of the system of automated design of biosensors is included. The classification of physical phenomena in the knowledge base is based on the energy-information model of circuits (EIMS). The automated system for designing of biosensors will expand the amount of specialized knowledge tenfold and reduce the time of creating new solutions by two to three times by reducing the volume of prototyping and full-scale tests due to choosing more efficient options and draft calculation of the significant characteristics of their conceptual models.

Conceptual design of biosensors

Design of biosensors refers to the field of interdisciplinary research, therefore, it is necessary to develop a unified systems approach that is invariant to the physical nature of the used phenomena and processes to create an automated system for conceptual design of such elements. It is appropriate to choose the fundamentals of non-equilibrium thermodynamics as the basis for the development of this approach. They allow to obtain a complete system of transfer equations of the phenomena of different physical nature and other laws, without opening their molecular mechanism. This article discusses the energy-information model of diffusion phenomena, as the processes of diffusion is the general type of the processes that is occurring in bioselective elements. A number of physical effects are described by this model. They are used in the conceptual design of electrochemical biosensors.