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Methods of Intelligent Control in Mechatronics and Robotic Engineering: A Survey

Iuliia Zaitceva, Boris Andrievsky

2022Englishintelligent controlmechatronicsroboticsmachine learningadaptive controlneural networks

Abstract

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Artificial intelligence is becoming an increasingly popular tool in more and more areas of technology. New challenges in control systems design and application are related to increased productivity, control flexibility, and processing of big data. Some kinds of systems require autonomy in real-time decision-making, while the other ones may serve as an essential factor in human-robot interaction and human influences on system performance. Naturally, the complex tasks of controlling technical systems require new modern solutions, but there remains an inextricable link between control theory and artificial intelligence. The first part of the present survey is devoted to the main intelligent control methods in technical systems. Among them, modern methods of adaptive and optimal control, fuzzy logic, and machine learning are considered. In its second part, the crucial achievements in intelligent control applications in robotic and mechatronic systems over the past decade are considered.

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Cite This Work

@article{afce2b19-fcf9-41cf-8454-619a3b1318b8,
  title={Methods of Intelligent Control in Mechatronics and Robotic Engineering: A Survey},
  author={Iuliia Zaitceva and Boris Andrievsky},
  year={2022},
  language={English}
}
TY  - JOUR
TI  - Methods of Intelligent Control in Mechatronics and Robotic Engineering: A Survey
AU  - Iuliia Zaitceva
AU  - Boris Andrievsky
PY  - 2022
LA  - English
ER  -

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