THEORETICAL FOUNDATIONS FOR THE SYNTHESIS OF COMPLEX CONTROL SYSTEMS USING ARTIFICIAL IMMUNE SYSTEM ALGORITHMS
Keywords:
artificial immune system, synthesis of optimal control, MIMO system, clonal selection algorithm, negative selection algorithmAbstract
This article formulates the theoretical foundations for the synthesis of complex control systems using algorithms of artificial immune control systems for complex objects: the canonical clonal selection algorithm (CLONALG), the negative selection algorithm (NSA). A multidimensional multi-connected object is presented as a complex system, for which optimal control is synthesized based on algorithms of artificial immune systems. The problem of synthesis of optimal control of a complex object is posed, for the solution of which expressions of typical regulators and quadratic quality criteria are formed. In order to minimize the selected quality criteria, CLONALG and NSA search algorithms were applied. The theoretical foundations of the synthesis of a complex system are built, including the steps of synthesis of optimal control for isolated subsystems of a complex system, the inclusion of interconnections and the application of the decoupling procedure to take into account these interconnections.
References
Бобиков А.И. Настройка весовых матриц ЗСУР регулятора с помощью биоинспирированных алгоритмов оптимизации // Вестник РГРТУ. – 2016. №55. – С. 77-83.
Bo X, Wen-Jing G. Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. – Springer, 2014. – 469 p.
Карпенко А.П. Современные алгоритмы поисковой оптимизации. Алгоритмы, вдохновленные природой. – М.: МГТУ, 2017. – 446 с.
Кушнир Н.В., Кушнир А.В., Анацкая Е.В., Катышева П.А., Устинов. Искусственные иммунные системы: обзор и современное состояние // Научные труды КубГТУ. – 2015. – №12. – 10 c.
Wang J., Song N., Jiang E., Xu D., Deng W., Mao L. The Application of the Particle Swarm Algorithm to Optimize PID Controller in the Automatic Voltage Regulation System. – Springer Singapore: Advanced Computational Methods in Energy, Power, Electric Vehicles and Their Integration, 2017. – P. 529-536.
Ali M., Koh S.P., Chong K.H. Design a PID Controller of BLDC Motor by Using Hybrid Genetic-Immune // Modern Applied Science. – 2011. – Vol. 5. – No.1 – P. 74-85.
Forrest S. Principles of a Computer Immune System // Proceedings of the Second New Security Paradigms Workshop. – 1997. – P. 75-82.
Ayara M., Timmis J., Lemos R., Castro L., Duncan R. Negative Selection: How to Generate Detectors // UK: In: Proceedings of the 1st International Conference on Artificial Immune Systems (ICARIS). – 2002. – Vol.1. – P. 89-98.
Marciniak J., Wawryn K.. An Artificial Immune Negative Selection Algorithm to Control Water Temperature in the Outlet of the Chamber // Poland: International conference on signals and electronic systems (ICSES). – 2018. – P. 236-241.
Ширяева О.И., Самигулин Т.И. Реализация SMART-технологии построения оптимальных систем на основе модифицированных алгоритмов // – Харків: Вісник Національного технічного університету. – 2020. – № 1 (3). – С.41-49.
