Mission critical decentralized resilient and intelligent control for networked heterogeneous unmanned autonomous systems (Conference Presentation)

Author(s):  
Hao Xu
IEEE Spectrum ◽  
1995 ◽  
Vol 32 (6) ◽  
pp. 55-62 ◽  
Author(s):  
K.M. Passino

Author(s):  
В. Б. Бетелин ◽  
Д. А. Моргун

Происходящие в мире события свидетельствуют о возрастании угрозы перехвата управления системами с критической миссией (СКМ). Приводятся конкретные примеры инцидентов, один из них — массовые отключения электроэнергии в Венесуэле. Обосновывается необходимость разработки технологии создания цифровых систем управления, обеспечивающей парирование угрозы перехвата управления и нештатного функционирования систем с критической миссией. В основе этой технологии — концепция цифровых двойников объектов управления цифровых систем управления этими объектами, включая все аппаратные и программные компоненты, а также интеллектуальные средства самоконтроля и самокоррекции функционирования элементной базы, вычислительной и коммуникационной техники, базового и прикладного программного обеспечения. There is an ongoing threat of control interception in mission-critical systems (MCS). Specific examples of such incidents are presented, one of them is the massive power outages in Venezuela. We specify the reasons for creating an approach to developing digital control systems for MCS resistant to control interception and abnormal functioning. This technology is based on the digital twin concept. A twin represents all the hardware and software components, as includes smart tools for the hardware, core and application software self-monitoring and self-correction.  


2021 ◽  
pp. 322-330
Author(s):  
Gennady P. Vinogradov ◽  
Igor A. Konyukhov ◽  
Aleksey A. Prokhorov

2021 ◽  
Author(s):  
Lisa Matsuyama ◽  
Rileigh Zimmerman ◽  
Casey Eaton ◽  
Kristin Weger ◽  
Bryan Mesmer ◽  
...  

Robotics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 64 ◽  
Author(s):  
Callum Wilson ◽  
Francesco Marchetti ◽  
Marilena Di Carlo ◽  
Annalisa Riccardi ◽  
Edmondo Minisci

The quest to create machines that can solve problems as humans do leads us to intelligent control. This field encompasses control systems that can adapt to changes and learn to improve their actions—traits typically associated with human intelligence. In this work we seek to determine how intelligent these classes of control systems are by quantifying their level of adaptability and learning. First we describe the stages of development towards intelligent control and present a definition based on literature. Based on the key elements of this definition, we propose a novel taxonomy of intelligent control methods, which assesses the extent to which they handle uncertainties in three areas: the environment, the controller, and the goals. This taxonomy is applicable to a variety of robotic and other autonomous systems, which we demonstrate through several examples of intelligent control methods and their classifications. Looking at the spread of classifications based on this taxonomy can help researchers identify where control systems can be made more intelligent.


2016 ◽  
Vol 2016 ◽  
pp. 1-2
Author(s):  
Chenguang Yang ◽  
Bin Xu ◽  
Hongbin Ma ◽  
Deqing Huang ◽  
Jing Na

2006 ◽  
Author(s):  
Ayse P. Gurses ◽  
Yan Xiao ◽  
Paul Gorman ◽  
Brian Hazlehurst ◽  
Grant Bochicchio ◽  
...  

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