Prof. Yongduan Song
Foreign Member of the Chinese Academy of Engineering, IEEE Fellow
Chongqing University, China

Speech Title: From Linearity to Nonlinearity: Breakthroughs and Practice in PID Control Architectures

Abstract: Over the century-long evolution of industrial automation, Proportional-Integral-Derivative (PID) control has established itself as a cornerstone of process control, owing to its simple structure, robust performance, and high reliability. However, as modern industrial systems increasingly exhibit large-scale, strongly nonlinear, time-varying, and multi-variable coupled characteristics, the conventional PID control paradigm — relying on fixed parameters — has gradually revealed its limitations in adaptability and intelligence.

In response to these challenges, this presentation adopts a dual perspective of "classical inheritance" and "intelligent leap" to explore effective pathways for endowing PID controllers with intelligent, autonomous, and self-adaptive capabilities. Moving beyond the single dimension of traditional parameter tuning, this work constructs a comprehensive empowerment framework that integrates intelligent algorithms, adaptive mechanisms, and nonlinearity and uncertainty compensation. Practical results demonstrate that intelligently empowered PID controllers not only retain the original advantages of low model dependency and ease of engineering implementation, but also achieve significant improvements in dynamic response quality, disturbance rejection, saturation suppression, and adaptability to complex operating conditions. This presentation aims to offer a viable pathway toward a new intelligent control ecosystem that balances theoretical depth with engineering value, and to promote the deeper integration and application of intelligent PID control technologies in Industry 4.0 and smart manufacturing.

Biography: Prof. Yongduan Song is Academician of the Chinese Academy of Engineering (Foreign Member), IEEE Fellow, Fellow of the Chinese Association for Artificial Intelligence (CAAI) and the Chinese Association of Automation (CAA). He serves as the Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), a top-tier international journal in artificial intelligence and the Founding Editor-in-Chief of Journal of Automation and Intelligence, a high-profile English-language journal supported by the China Sci-Tech Journal Excellence Action Plan (High-Starting Point New Journals). He also serves as Director of the Technical Committee on Trustworthy Control Systems, CAA. He previously held the position of Director of the "Collaborative Systems" Center at the U.S. National Institute of Aerospace and was recognized as a Langley Distinguished Scientist. He has led over 30 major research projects, including key programs of the National Natural Science Foundation of China, National Key R&D Programs of the Ministry of Science and Technology, and provincial/ministerial-level initiatives.

Prof. Honggui Han
Dean of the School of Computer Science
Beijing University of Technology, China

Speech Title: Multi-objective dynamic collaborative optimization for the municipal wastewater treatment process

Abstract: Municipal wastewater treatment is an effective way to protect the environment and realize water resource recycling. However, due to the multi-processes, multi-working conditions, time-varying and other characteristics of municipal wastewater treatment process, optimal control based on a single scale, a single level, and a single goal cannot guarantee the optimum of the overall operation. Multi-objective collaborative optimization control achieves multi-objective optimization between local and global, short-term and long-term, and efficiency and safety in the municipal wastewater treatment process by constructing performance indicators at different time scales and designing a multi-conflict objective dynamic optimization method. It solves the problem of real-time dynamic optimization setting of key variables in the municipal wastewater treatment process, and effectively reduces the operating cost.

Biography: Honggui Han, professor, doctoral supervisor, and dean of the School of Computer Science. He has been engaged in research on intelligent control of complex systems, and has been selected for the National Science Fund for Distinguished Young Scholars, the National Science Fund for Excellent Young Scholars, the Young Beijing Scholar, the Young Scientist of the Chinese Automation Society, and the Outstanding Young Scientist of Beijing Universities, etc. As a result of the research, he has published more than 100 academic papers and written 5 books; he has obtained more than 60 authorized Chinese/American invention patents, has presided over/participated in the formulation of more than 10 national/group/local standards. He has won the second prize of the National Science and Technology Progress Award, the first prize of the Ministry of Education Science and Technology Progress Award, and the first prize of the Wu Wenjun Artificial Intelligence Science and Technology Progress Award, etc. He is currently the director of the "Digital Community" Engineering Research Center of the Ministry of Education and the director of the Beijing Key Laboratory of "Computational Intelligence and Intelligent Systems". He also serves as an editorial board member of journals such as China Science: Technical Sciences, IEEE Transactions on Cybernetics, etc.

Prof. Lipeng Wang

Harbin Engineering University, China

Speech Title: Nonlinear Control and Applications under Fault and Disturbance Environments

Abstract: Under fault and disturbance environments, system dynamics often exhibit strong nonlinearity, time-varying characteristics, and uncertainties, making it difficult for traditional linear control methods to guarantee control accuracy and stability. Therefore, developing effective nonlinear control methods is of great significance for enhancing the safety and mission reliability of complex platforms. This report addresses this issue and is organized as follows: Integrated fault reconstruction and fault-tolerant control, SMC based on four-quadrant switch and NMPC, Super-twist sliding mode and RBFNN, and Event-triggered optimal control. The application effects of these methods on platforms such as rotorcraft, fixed-wing aircraft, and ships are also introduced. Each method presented in this report originates from practical problems encountered in the control processes in real-world systems. These practical problems are abstracted into mathematical models within nonlinear control theory, and specific controllers are designed using methods such as sliding mode control, model predictive control, and robust control to accomplish nonlinear control tasks for plants under faults and disturbances.

Biography: Lipeng Wang, professor, doctoral supervisor at the College of Intelligent Science and Engineering in Harbin Engineering University. He received his bachelor's, master's, and doctoral degrees from Harbin Engineering University. His research focuses on perception and control of complex systems. He has led three projects funded by the National Natural Science Foundation of China, one project funded by the Natural Science Foundation of Heilongjiang Province, and other research projects. He has received multiple awards, including one First Prize for Scientific and Technological Progress at the provincial and ministerial level, one Special Prize and one First Prize for Scientific and Technological Progress from the China Institute of Navigation. He has published more than 40 high-level papers as the first author or corresponding author, and three monographs as the first author.