At present, the study of uncertain complex systems has penetrated into many fields, and has become one of the research hotspots. Synchronization/control of complex systems plays a crucial role in many engineering problems, such as secure communication, image processing and generation of harmonic oscillators. In addition, both ability and speed for controlling or synchronizing complex systems are directly related to the stability of the whole system and the transmission efficiency of the network, which indicates a very important academic value and a research significance. Many research achievements in the topic of control/synchronization of complex systems have been made in the recent decades, but the relevant researches were almost limited to relatively accurate mathematical models. Thus, it yields an urgent requirement to develop more innovative ideas and meaningful findings to tackle the control and synchronization issues of more complex nonlinear systems. Moreover, the application of these synchronous control methods in practical systems is also worthy of further research, such as secure communication, aerospace, robots, ships, multi-agent systems, artificial neural networks and so on.
This Research Topic aims to call on the research community to explore new methods of synchronization and control of complex systems, and discuss how these methods can be applied in engineering, physics, economics and other systems.
The principal objective of this Research Topic is to share the research work of the latest advances in control/synchronization of complex systems and their applications. The area of interest is expansive and includes several key categories as follows:
-Modeling of complex system
- Synchronization of chaotic system
- Nonlinear dynamical system
- Robust control of complex system
- Adaptive control of complex system
- Stability analysis
- Fractional-order complex system
- Neural networks
- Application of complex system
- Fuzzy control
- Adaptive control
- Artificial neural networks
- Confidential communication
- Robotic manipulators control
- Aircraft formation
At present, the study of uncertain complex systems has penetrated into many fields, and has become one of the research hotspots. Synchronization/control of complex systems plays a crucial role in many engineering problems, such as secure communication, image processing and generation of harmonic oscillators. In addition, both ability and speed for controlling or synchronizing complex systems are directly related to the stability of the whole system and the transmission efficiency of the network, which indicates a very important academic value and a research significance. Many research achievements in the topic of control/synchronization of complex systems have been made in the recent decades, but the relevant researches were almost limited to relatively accurate mathematical models. Thus, it yields an urgent requirement to develop more innovative ideas and meaningful findings to tackle the control and synchronization issues of more complex nonlinear systems. Moreover, the application of these synchronous control methods in practical systems is also worthy of further research, such as secure communication, aerospace, robots, ships, multi-agent systems, artificial neural networks and so on.
This Research Topic aims to call on the research community to explore new methods of synchronization and control of complex systems, and discuss how these methods can be applied in engineering, physics, economics and other systems.
The principal objective of this Research Topic is to share the research work of the latest advances in control/synchronization of complex systems and their applications. The area of interest is expansive and includes several key categories as follows:
-Modeling of complex system
- Synchronization of chaotic system
- Nonlinear dynamical system
- Robust control of complex system
- Adaptive control of complex system
- Stability analysis
- Fractional-order complex system
- Neural networks
- Application of complex system
- Fuzzy control
- Adaptive control
- Artificial neural networks
- Confidential communication
- Robotic manipulators control
- Aircraft formation