Galyna Kondratenko

Slip displacement sensors for intelligent robots: Solutions and models

This paper discusses the design of modern tactile sensor systems for intelligent and adaptive robots. It provides information on three approaches for using slip displacement signals (for correction of claiming force, for identification of manipulated object mass and for correction of robot control algorithm). The study presents the analysis of different methods for slip displacement signals detection, as well as new sensors schemes, mathematical models and correction methods. Special attention is paid to investigations of developed by authors sensors with the capacity, magnetic sensitive elements and with automatic adjustment of claiming force.

Fuzzy decision support systems in marine practice

The article is a review of the perspective methods and approaches to the design of fuzzy decision support systems (DSS) with the application of discrete fuzzy inference engine. The authors also developed a two-stage method for fuzzy rule base (RB) correction in the case of changing the structure of the input vector. In addition, the fuzzy DSS with a hierarchical structure for the best selection of the marine delivery company was developed. Simulation results confirm the effectiveness and feasibility of fuzzy DSS structure with variable input coordinates vector, in particular, in marine practice.

Fuzzy Decision Making System for Model-Oriented Academia/Industry Cooperation: University Preferences

This paper discusses the effective models of cooperation of universities and IT companies, as well as the hierarchic approach towards projecting certain decision making support systems (DSS) based on fuzzy logic. Special attention is paid to fuzzy DSS as an advisor in choosing the most appropriate cooperation model for a certain department of universities eager to become partners within the frames of future cooperation with a certain IT company. The article features hierarchic structure, results of rule bases and DSS software based on the approximation of fuzzy systems with discrete output. It also contains the results of imitational DSS modeling based on the elaborated DSS developing the most rational model of cooperation for a university party of the cooperation of the “University—IT company” type.

Synthesis and Optimization of Green Fuzzy Controllers for the Reactors of the Specialized Pyrolysis Plants

This paper presents the developed by the authors generalized step-by-step method of synthesis and optimization of green fuzzy controllers (FC) for the automatic control systems (ACS) of the reactor’s temperature of the specialized pyrolysis plants (SPP). The proposed method gives the opportunity to synthesize and optimize Mamdani type green FCs of the temperature modes of the SPPs reactors that provide (a) high accuracy and quality indicators of temperature control, (b) low energy consumption in the process of functioning as well as (c) relatively simple software and hardware implementation. The initial synthesis of the structure and parameters of green FCs is implemented on the basis of expert assessments and recommendations. Their further optimization for improving the quality indicators, reducing energy consumption and simplification of soft/hardware realization is carried out using specific optimization procedures by means of mathematical programming methods. In order to study and validate the effectiveness of the developed method the design of the Mamdani type green FC for the temperature ACS of the pyrolysis reactor of the experimental SPP has been carried out in this work. The developed green FC has a relatively simple hardware and software implementation as well as allows to achieve high quality indicators of temperature modes control at a sufficiently low energy consumption, that confirms the high efficiency of the proposed method.

Intelligent Decision Support System for Selecting the University-Industry Cooperation Model Using Modified Antecedent-Consequent Method

This work is devoted to the analysis and selection of the most rational model of the university/IT-company cooperation (UIC) using intelligent decision support systems (DSSs) in the conditions of input information uncertainty. The modification of a two-cascade method for reconfiguration of the fuzzy DSS’s rule bases is described in details for situations when the volume of input data can be changed. Authors propose an additional observer procedure for checking the fuzzy rule consequents before their final correction. The modified method provides (a) structural reduction of the rule antecedents, (b) correction of the corresponding consequents in an interactive mode and (c) avoiding the results’ deformation in the decision making process with variable structure of input data. Special attention is paid to the hierarchically organized DSSs (with variable input vector and discrete logic output) and to design of the web-oriented instrumental tool (WOTFS-1). The simulation results confirm the efficiency and expediency of using (a) the software WOTFS-1 and (b) modified method of fuzzy rule base’s antecedent-consequent reconfiguration for the efficient selection of the rational model of academia-industry cooperation.

Multi-criteria Decision Making and Soft Computing for the Selection of Specialized IoT Platform

The task of the appropriate selection of the specialized Internet of Things (IoT) platform is very relevant today. The complexity of the selection process is due to (a) the large number of IoT platforms, which are available on the IoT services market, and (b) the variety of services and features, which they offer. In this paper, the multi-criteria decision making (MCDM) and the soft computing approaches for choosing the specialized IoT platform are considered. Authors illustrate solving MCDM problem using the linear convolution method with simple ranking approach to forming weight coefficients for criteria. MCDM methods have some limitations: (a) the need to take into account weight coefficients of the criteria; (b) the composition of the Pareto-optimal set of alternative decisions; (c) the lack of ability to change the dimension of the vector of alternatives and criteria in real time; (d) significant impact of weight coefficients that the expert determines on the result. Thus, the authors propose to use the soft computing approach, in particular, Mamdani-type fuzzy logic inference engine for selection of the specialized IoT platform. Relevant factors (reliability, dependability, safety, and security of IoT platforms) are considered as the most important ones for decision making in the IoT platform selection processes. In addition, analysis and research of the influence level of various factors on the selection of specialized IoT platform have been carried out. Special cases of choosing the specialized IoT platform with confirmation of the appropriateness of the using soft computing approach are discussed.

Комплекс завдань моніторингу та автоматичного управління мобільними роботами для вертикального переміщення

There have been analyzed and formalized the tasks of monitoring and automatic control of mobile robots (MR) for their movement and execution of various types of technological operations on inclined and vertical ferromagnetic surfaces. Generalized structure of a mobile robotic complex is shown with consideration to its main subsystems. The paper presents critical analysis of the current state of the problem of development of universal structures of MRs for the various types of technological operations and elaboration of computerized systems for monitoring and control of MR movement. In particular, there is provided a review of wheeled, walking and tracked MRs with pneumatic, vacuum-propeller, magnetic and magnetically operated clamping devices to grip vertical and ceiling surfaces. The constructive features of the crawler MR with a magnetic clamping device capable of moving along inclined ferromagnetic surfaces are considered. The basic technical parameters of the MR are shown for the further synthesis of computerized monitoring and automatic control systems. Formalization of monitoring and control of the MR positioning at the processing of large ferromagnetic surfaces is considered from the point of view of the control theory.

Two-stage method of fuzzy rule base correction for variable structure of input vector

The paper analyzes the existing methods and approaches to correcting bases of fuzzy rules of decision support systems (DSS). There was developed and implemented a two-stage method of fuzzy rule base correction for hierarchically-organized DSS with discrete logic output at variable structure of input vector. The appropriate method interactively provides reduction of database rules structure and correction of rules consequents at changing the number of input data, which enables to avoid results deformation in decision making. The feature of this method is the ability to process fuzzy input data with a high level of uncertainty, given in the form of fuzzy sets. Simulation results confirm the effectiveness and feasibility of the two-stage correction method of fuzzy rule bases of hierarchically-organized DSS developed by the authors, including the choice of models of cooperation within the consortium of the “University — IT company”.

Knowledge-Based Decision Support System with Reconfiguration of Fuzzy Rule Base for Model-Oriented Academic-Industry Interaction

In this work the current state of the problem, which consists in choice the rational model of academic-industry interaction such as “University – IT-company” is analyzed. To solve this problem it is developed and researched the intelligent decision support system (DSS) based on fuzzy logic for multi-criterion evaluation the most rational model of academic-industry interaction such as “University – IT-company” in case of changing dimension of input coordinates vector.