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7Central Asian Research Journal For Interdisciplinary Studies (CARJIS)
ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
SOME PROBLEMS OF AUTOMATIC CONTROL AND MANAGEMENT IN
CONDITIONS OF UNCERTAINTY
N.R. Yusupbekov, Sh.M. Gulyamov, E.E. Ortiqov
Tashkent State Technical University named after Islam Karimov E-mail: [email protected]
ABSTRACT
Some problematic issues of automatic control and management of complex technological processes and productions in the conditions of internal and external parametric uncertainty of models of research objects are discussed. Classification of types of uncertainties of models of dynamic objects of research is carried out.
Keywords: Classifications of types of uncertainty in the model of dynamic objects of control and management.
АННОТАЦИЯ
Обсуждается некоторые проблемные вопросы автоматического контроля и управления сложными технологическими процессами и производствами в условиях внутренней и внешней параметрической неопределенности моделей объектов исследования. Выполнена классификация видов неопределенностей моделей динамических объектов исследования.
Ключевые слова: Классификация видов неопределённости модели динамических объектов контроля и управления.
INTRODUCTION
Complex control systems have uncertainties that can be generated both by the system itself and be caused by external exciting influences, which makes it extremely difficult to adequately control an object using classical methods of automatic control. In this regard, for control under conditions of uncertainty, it is advisable to use the methods and algorithms of the modern theory of automatic control and, in particular, the theory of adaptive systems or the theory of robust control. Regulators synthesized on the basis of the mentioned theories are able to neutralize the negative impact of uncertainty.
The theory of constructing robust controllers based on fuzzy set algorithms favorably stands out from the well-known areas that allow controlling dynamic
Central Asian Research Journal For Interdisciplinary Studies (CARJIS)
ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
objects under uncertainty. Features of the synthesis of controllers based on fuzzy logic make it possible to attribute them to the class of robust controllers based on a matrix structure. The latter circumstance suggests that the algorithm for generating a control action can be calculated in parallel, while the rule base contained in the controllers allows you to implement protective algorithms directly into the controller, and the introduction of a protection map into the controller will significantly increase the security of the system.
The topicality of the work related to the development of modern advanced (or advanced) control systems, known as Advanced Process Control and Optimization (APC) - systems based, in particular, on fuzzy logic elements, is confirmed by the need to control objects distributed in space. Especially important is the development of APC advanced control systems that meet the current stage of development of technical systems in terms of functionality and safety.
Some problems of control and management under uncertainty
The mentioned classical methods of analysis and synthesis of automatic control systems are based on the postulate that the synthesized mathematical model is exactly describes the technological process taking place in the control object [1-4]. Methods that are based on the above assumption are referred to the arsenal of the classical theory of automatic control, which is characterized by a more critical approach to the design of control systems and mathematical models of control objects, when some characteristics of the object may be initially unknown or change during operation and when it can be argued about uncertainty of the mathematical model of the control object [5-10].
This very uncertainty can be tolerated up to a certain level, at which classical control methods can be applied. If the uncertainty exceeds the level allowed for the classical theory, then its methods become inapplicable or do not allow achieving the specified control indicators [11]. In such cases, it is required to apply non-classical methods of analysis and synthesis, both for an individual regulator and for the entire control system as a whole. These methods should take into account the incomplete model of the object and the need and possibility of changing the characteristics of the object [12].
Let us turn to the main types of uncertainties of mathematical models of objects [13-21].
Central Asian Research Journal For Interdisciplinary Studies (CARJIS)
ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
Parametric uncertainty. This uncertainty implies that the unknowns are the constant parameters of the object. The values of the latter can be either unknown in advance or change during the operation of the object. In some cases, the values of the parameters of a real object may differ significantly from those implemented in the mathematical model. In such cases, correction is used (preferably automatic, but manual is also possible) of the measurement results, depending on the nature of the influencing factor.
Signal uncertainty. This uncertainty implies that the object is affected by a signal that cannot be measured. It can also be a signal with initially unknown parameters of external or internal origin, which are usually referred to as disturbing influences. Such uncertainties appear when situations arise in which a spurious signal is superimposed on the measured signal of the object of control or management.
Functional uncertainty. This uncertainty implies that the mathematical model of the control object contains unknown functional dependencies: if any function is taken into account in the model, then the conditions that indirectly affect the function cause uncertainty.
Structural uncertainty. This uncertainty implies that the structure of the mathematical model is not fully known. Typically, this is the smaller dynamic order of the model relative to the object itself. This phenomenon is called parasitic dynamic component.
Structural uncertainty can also be caused by unknown or unaccounted dependencies in the object model.
In general, uncertainties appear even at the stage of system synthesis. They can be generated by the lack of complete comprehensive information about the object of regulation, the conditions in which the object must operate, the spread of technological parameters determined during production, as well as the lack of a complete generalized mathematical model.
In addition, there are uncertainties that appear during the operation of the control object due to, for example, wear of moving parts, changes in the structure of the electrical conductor with temperature changes, changes in the environmental conditions. Together, all the uncertainties create serous management problems in the face of uncertainty.
Central Asian Research Journal For Interdisciplinary Studies (CARJIS)
ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
CONCLUSION
When developing an automatic control system for a regulated object, it is necessary to determine whether it is permissible or not to use classical control methods under these specific conditions of uncertainty. The literature [14-16] reflects some theories that make it possible to determine the possibility of using classical controllers.
Theory of roughness of properties. The theory says that it is necessary to determine the conditions under which the properties of a closed system do not change when measuring its mathematical model.
The theory of sensitivity. The theory uses the hypothesis of small deviations of parameters relative to predetermined values. The theory works with parametric uncertainty.
Theory of interval systems. In this theory, sets of uncertainties are considered, which are independent objects, and the Hurwitz stability condition is verified for each.
Theory of singularly perturbed systems. The theory makes it possible to study the monitoring and control system taking into account parasitic disturbances. After analyzing the object under study, one of the mentioned theories can show that the classical method is not suitable for system synthesis. In this case, it is necessary to use the theory of robust or adaptive systems.
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ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
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ISSN (online): 2181-2454 Volume 2 | Issue 10 |October, 2022 | SJIF: 5,965 | UIF: 7,6 | ISRA: JIF 1.947 | Google Scholar |
www.carjis.org DOI: 10.24412/2181-2454-2022-10-65-70
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