Topic: Control and Optimization for Stochastic Systems

Stochastic systems, influenced by unpredictable factors in the real world, such as changes in the external environment and the internal complexity of the systems, have been applied in widespread fields such as finance, communication networks, aerospace, and mechanical engineering systems. However, traditional deterministic methods are ineffective when dealing with these random factors. Over the past decades, in order to reduce the impact of uncertainties, numerous scholars have adopted various techniques to analyze and study the stochastic factors within systems. These techniques include stochastic differential equation theory, operator spectrum techniques, H-representation techniques, etc. In recent years, with the development of computer science, network control methods, machine learning theory, and other theories have been used to investigate stochastic systems. This has introduced new opportunities and challenges, necessitating innovative approaches and theories to address control and optimization problems.

This Special Issue delves into the realm of control and optimization for stochastic systems, with a focus on theoretical research and engineering applications. We invite contributions that are dedicated to exploring cutting-edge theories and practical applications in this field. Researchers are encouraged to submit original articles, reviews, and case studies, with an emphasis on innovative methodologies and theoretical contributions. Manuscripts on a wide spectrum of topics related to the control and optimization for stochastic systems are welcome, including but not limited to:
• Stochastic Systems;

• Fuzzy Systems;

• Complex Networks and Dynamic Systems;

• Nonlinear Models and Systems;

• Multi-agent Systems;

• Optimization and Applications of Control Theory;

• Stochastic Linear-Quadratic Control;

• Stochastic Cooperative Games;

• Robust Control;

• Adaptive Control of Stochastic Systems.

30 Apr 2024