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Аbstract. The paper presents the methodology for selecting the most optimal alternative of an energyefficient control system for a complex process system. The proposed methodology is may help to solve structural synthesis problems. Designing a control system is a set of interrelated operations aimed at achieving a specific outcome. The implementation of such project might involve uncertainties and risks, high costs, many stages and considerable time consumption, the need to have a well-coordinated team of executors, as well as no guarantee that there wiil be the expected outcome. The choice of a project management methodology and a strategy depends on the type of the process system and the project implementation objectives, the nature of uncertainties and risks, the possibility of using information technology and parallel design.Both project risks and design costs depend on the number of alternatives considered during design stages. Therefore, for project management it is necessary to use design process models that take into account the number of alternatives and their effectiveness at each stage of design work. In general, a design process can be described by a functional model in IDEF0 format supplemented by decision-making nodes.The method of evaluating the effectiveness of alternatives is based on the method of dynamic variation, which assumes that each design stage has a formed group of various alternatives that begin to be developed in parallel. After each stage, there is an expert evaluation session with the following decision on the significance of different alternatives in a group.As an example, the paper describes using the dynamic variation method for developing a control system for a six-section precision furnace for heat treatment of thermistor workpieces in the air. From a control point of view, it is a typical MIMO system with complex relations between inlets and zones.

At the manufacturing plants producing thermal insulation materials that are used in a climate of the Arctic, non-destructive testing of thermo-physical properties to ensure the quality of the products is necessary. Therefore, the use of intelligent information and measuring system with appropriate algorithmic software to control the thermo-physical properties of the objects under study is important and relevant. The aim of research is to improve the accuracy and efficiency of determining thermo-physical properties as a result of solving the classification and image recognition problems of the studied objects in production and operation to prevent deterioration of thermal insulation properties under the effect of external influential factors. Image recognition algorithms are proposed for cases when the processed information is reliable or falls into the category of fuzzy. The algorithm of decision-making in the intelligent measuring system for the choice of the non-destructive testing method of thermo-physical properties in accordance with the class of materials under study is presented. The results of experimental studies of the intelligent information and measuring system implementing the developed algorithms for image classification and recognition of the studied objects are represented, these results confirming the increase in the accuracy of non-destructive testing in thermo-physical properties of materials.

The paper focuses on the problem of energy-saving control of a large low-pressure air separation plant with a turbo-expander. The plant is designed for simultaneous production of nitrogen, oxygen and argon and operates at variable performance over a time interval when the need for air separation products is repeatedly changed. The purpose of the research is to improve the efficiency of the air separation plant, in terms of minimizing energy consumption for air separation over a time interval, using destabilizing optimization algorithms for the operating modes of its rectification subsystem, the latter being the core of the proposed plant. The study introduces the author's "concept of destabilization", which consists in expanding the range of feasible solutions to the problem by replacing in its statement some constraints like equalities with inequality constraints. This is technologically equivalent to purposefully changing some parameters within acceptable limits instead of stabilizing them, which provides an additional effect over a time interval. The authors developed methods and algorithms for controlling an object over a time interval, which provide for all possible changes in the performance of various target air separation products with a linear dependence of the optimality criterion on additional control actions resulting from destabilization. A specific example demonstrates the use of destabilization control algorithms for solving the problem of optimizing the modes of the rectification subsystem of the air separation plant over a certain time interval with an estimate of the effect obtained. Using the proposed approach and making structural changes to the existing equipment of the rectification subsystem of the air separation plant, we can significantly increase the resulting effect. Destabilization can be fully applied to other complex technological objects with liquid capacities and when a change in the liquid levels is acceptable within certain limits. Further research is needed to find out how plant performance and the time of the plant constancy influence the degree of the resulting effect, as during the plant operation the need for separation products, the moments of their switching and the time of constant performance intervals repeatedly change.