Change Control and Evaluation for Synchronous Evolution of Production and Supply Chain Systems

Chair: Chen Peng, Shanghai University

Supply chain management mainly refers to a management mode of product manufacturing, transportation, distribution and sales by integrating suppliers, manufacturers, distributors and warehouses to reduce the cost of the whole supply chain. As an important support for modern economic development, supply chain plays an extremely important role in production and manufacturing. However, during the process of synchronous evolution of product and supply chain, design change is unavoidable and indispensable due to uncertain demands and unexpected events such as network attack, trade war, natural disasters, epidemic disease of COVID-19 and etc. This inevitably results in information distortion, mechanism unclearness and lack of change control. Therefore, how to redesign product and supply chain system constitutes a challenge for network collaborative manufacturing process. At present, it is a crucial task to break the bottleneck of transmission effect analysis for supply chain systems, to solve the difficult problems of utility assessment and behavior prediction, and to realize the change control for supply chain system under uncertain environment. The primary objective of this IEEE RASSE 2021 invited session is to provide up-to-date discussions on technical trends and intelligent methodologies in modeling, utility assessment analysis and change control design of the product and supply chain synchronous evolution systems. Of particular interest the papers in this special session are devoted to the development of data driven based methodologies for modeling, analysis and control of the product and supply chain synchronous evolution systems, the development techniques of the change effect propagation for the multi-agent based simulation system and data visualization system. The contributions to this special session are expected to provide the latest results in modeling, utility assessment analysis and change control design of the product and supply chain synchronous evolution systems. Topics to be covered in this special issue include, but are not limited to: (1)Construction of product design knowledge map for synchronous evolution of product and supply chain; (2)The product design method framework based on synchronous evolution of product and supply chain; (3)Modeling & simulation of the change effect propagation dynamics; (4)Change effect propagation analysis and prediction method based on synchronous evolution of product and supply chain; (5)The influence mechanism of change effect propagation on product service performance and supply chain architecture; (6)Development of multi-agent simulation system for change effect propagation; (7)Development of system for data visualization of product and supply chain system; (8)Assistant decision application for change control scheme evaluation.

Network-Based Control and Autonomous Systems

Chair: Yu-Long Wang Wang, Shanghai University

This special session is organized by the following organizers: Professor Yu-Long Wang, Shanghai University Professor Dong Yue, Nanjing University of Posts and Telecommunications Professor Chen Peng, Shanghai University Nowadays, data networking technologies have been widely applied in industrial and military scenarios due to advancements in communication technologies such as fieldbus or wireless network. These control applications are usually called network-based control systems, which can provide several advantages compared with traditional control applications. Network-based control has received much attention from the control community for industrial automation and has found applications in a broad range of areas, such as mobile sensor networks, internet of things, motion control of autonomous systems, industrial robotics, multi-agent systems, cyber-physical systems, human-machine-systems, energy systems, and et al. This special session is to report recent developments on network-based control systems, automotive systems and their applications. Topics of interest are included but not limited to: » Systems Science » Systems Engineering » Systems-of-Systems » Cyber-Physical Systems » Cyber-Physical System Security » Systems Architecture » Systems Verification » Modeling & Simulation » Model-Based Systems Design » Human-Machine-Systems (Industry 5.0) » Large-Scale Systems Integration » Energy Systems » Space and Communication Systems » Automotive Systems » Autonomous Systems » Transportation Systems » Environmental Systems

Special Section on Advanced Control and Modelling of Complex Systems

Chair: Kun Zhang, Nantong University

The investigation of complex systems in a unified manner is recognized during the last few years as a new and very promising scientific discipline. Therefore, a wide range of interdisciplinary methods and techniques should be applied and, at the same time, new tools should be invented to extract hidden and valuable information from the complex systems. The main aim of this special section is to present control algorithms and modelling techniques for analysing complex systems.Various complex systems are widely applied in industries, bio-medicals, and transportations. Control technology and modeling identification are some of the key issues for complex systems to achieve the desired high performance. However, for those complex systems, mechanism complicacy and uncertainties are much more obvious and bring significant negative effects. Thus, effective modeling, identification, and intelligent analysis are necessary for complex systems. advanced control strategies and big data based modeling are the corresponding solutions to improve system performance. Advanced modeling and control are some of the key points for those complex systems, where complicacy and uncertainty become more and more challenging to pursue higher system performance. This special section contains the papers addressing the recent theoretical advances and experimental results on the topics such as neural systems, information and computation theory, signal processing, mechatronics, bioengineering, and complex adaptive systems.