Advances in Stability Analysis and Intelligent Control for Stochastic Systems

Chair:	Co-Chair:
Weihai Zhang Shandong University of Science and Technology, China	Tianliang Zhang Qingdao University of Technology, China

Key Words: Stochastic Systems, Intelligent Control, Stability Analysis, Machine Learning in Control

Information: The stability analysis of stochastic systems and intelligent control is a frontier field in contemporary control theory, especially with the high demands for system stability in complex and uncertain environments. With the rapid development of intelligent control technologies, ensuring the robustness of systems under stochastic disturbances has become an important challenge in both theory and practice. This special session is aimed at researchers, engineers, and students in the fields of control theory and intelligent control technologies, particularly those who focus on the stability analysis of stochastic systems and the application of intelligent control. The research objective of this session is to explore how advanced stability analysis and intelligent control techniques can address uncertainties and disturbances in stochastic systems. Through this research, the aim is to explore effective methods to improve system stability and optimize control strategies in practical applications, thereby advancing the theory and technology in this field.

Topics of interest include but are not limited to: 

• Development of adaptive learning control methods for stochastic systems
• Robustness analysis and performance guarantees in the presence of random disturbances
• Stochastic optimal control and adaptive learning control
• Lyapunov-based approaches for stochastic adaptive control
• Convergence and stability analysis in stochastic environments
• Exploration of deep learning and reinforcement learning for stochastic systems

Submission Deadline: April 28, 2026 (the first round)