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Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/35393
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Документ Optimal design of intelligent control systems of steam turbine using genetic algorithms(Institute of Information Theories and Applications FOI ITHEA, 2009) Fedyanyna, Khrystyna; Kucher, Ievgeniia; Severin, Valeriy PetrovichOne of the basic engineering problems of the automatic control systems synthesis for steam turbines is systems quality indices optimization task. The features of such task are defined by plenty of control systems structural parameters, complication of quality indices formalization and calculation, the systems models high order. The greatest difficulty of the control system synthesis is optimization models and methods design. The paper purpose is to develop models and methods for optimum design of the intelligent automatic control systems of atomic power station steam turbine using genetic algorithms. The steam turbine automatic control system is applied to stabilize turbine rotor frequency with high precision. The intelligent steam turbine control system includes a steam turbine, frequency sensor, intelligent frequency regulator, electro-hydraulic automatic drive and turbine adjusting valve. Input signals on an automatic drive can be given by the steam pressure regulator through the turbine management mechanism or by the electric power regulator. Assumptions substantiated to model the automatic control system and automatic drive as executive link of control system. The automatic drive diagram of principle includes electro-hydraulic transformer, sleeve valve, servomotor, position sensors and electronic part. In the paper were built the mathematical models of automatic drive and steam turbine, the models permanent parameters values were calculated, the mathematical models of the automatic control system were developed in state space with the intelligent frequency regulator, the regulator parameters were optimized with system quality indices using genetic algorithms.Документ Optimal synthesis of intelligent control systems of atomic power station using genetic algorithms(Institute of Information Theories and Applications FOI ITHEA, 2009) Jafari Henjani, Seyed Mojtaba; Severin, Valeriy PetrovichThe paper is devoted to the development of a perspective concept of atomic station power block intelligent automatic control systems synthesis on the basis of mathematical models and numeric methods of vector optimization of systems quality indexes using genetic algorithms. The methods for calculation of direct quality indexes and improved integral quadratic estimates have been created. The step-by-step principle of transition to the domain of system stability has been based. There have also been suggested vector objective functions including stability conditions and taking into consideration quality indexes priorities. The reliable genetic algorithms for vector objective functions optimization have been suggested. Mathematical models in the state space for intelligent automatic control systems of nuclear reactor and steam generator have been worked out. The quality indexes optimization of power block intelligent control systems has been carried out, which allowed to estimate various controller types efficiency.Документ Application of Genetic Algorithms to Vector Optimization of the Automatic Control Systems(Institute of Information Theories and Applications FOI ITHEA, 2009) Severin, Valeriy PetrovichMethods for calculation of quality indexes for automatic control systems are presented. For the optimization of quality indexes defined only in a stability domain a vector objective function of varied parameters of the system is proposed. The stepwise principle of successive satisfaction of constraints for the passage into the definition domain of quality indexes is considered, as well as a rational mechanism of its realization in the form of the priority optimization of the vector objective function. For the optimization of the vector objective functions genetic algorithms as vector optimization methods are presented. Their application allows one to steer the optimization process from any initial point of the space of varied parameters into the stability domain of the system and to find the optimum of the quality indexes in this domain. The efficiency of the proposed application of vector genetic algorithms for the quality indexes optimization is confirmed by computational experiments.