Zhipeng Li, Yanqian Wang, Guangming Zhuang, Zhibo Yang
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引用次数: 0
Abstract
This paper mainly studies the design of asynchronous controllers for positive singular semi‐Markov jump systems with performance under the dynamic‐memory event‐triggered. The positive singular semi‐Markov jump system model is established for the first time. And the dynamic‐memory event‐triggered transmission protocol is used to reduce network transmission pressure. Then, a unified cyber‐attack framework that includes DoS attacks and spoofing attacks is established. A simple hidden Markovian model (HMM) model is used to describe the asynchronous phenomena between the controller and the system. Considering the situation where all data cannot be accurately obtained in reality, a simple HMM is set as a partially unknown conditional probability matrix. Based on stochastic Lyapunov functional, the stochastically admissible conditions for the closed‐loop systems are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed method.
期刊介绍:
The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application.
Published six times a year, the Journal aims to be a key platform for control communities throughout the world.
The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive.
Topics include:
The theory and design of control systems and components, encompassing:
Robust and distributed control using geometric, optimal, stochastic and nonlinear methods
Game theory and state estimation
Adaptive control, including neural networks, learning, parameter estimation
and system fault detection
Artificial intelligence, fuzzy and expert systems
Hierarchical and man-machine systems
All parts of systems engineering which consider the reliability of components and systems
Emerging application areas, such as:
Robotics
Mechatronics
Computers for computer-aided design, manufacturing, and control of
various industrial processes
Space vehicles and aircraft, ships, and traffic
Biomedical systems
National economies
Power systems
Agriculture
Natural resources.