Cooperative control in production and logistics. (2015)

• Record Type: Journal Article
• Authors: Monostori, László; Valckenaers, Paul; Dolgui, Alexandre; Panetto, Hervé; Brdys, Mietek; Csáji, Balázs Csanád
• Is Part Of: Annual reviews in control. Volume 39(2015)
• Page Start: 12
• Page End: 29
• Publication Date: 2015
• Subjects: Automatic control -- Periodicals; Periodicals; 629.805
• DOI: 10.1016/j.arcontrol.2015.03.001
• Languages: English
• ISSNs: 1367-5788

Abstract

Abstract: Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety of interacting, interdependent elements. A paradigm shift, e.g., novel organizing principles and methods, is needed for supporting the interoperability of dynamic alliances of agile and networked systems. Several solution proposals argue that the future of manufacturing and logistics lies in network-like, dynamic, open and reconfigurable systems of cooperative autonomous entities. The paper overviews various distributed approaches and technologies of control engineering and ICT that can support the realization of cooperative structures from the resource level to the level of networked enterprises. Standard results as well as recent advances from control theory, through cooperative game theory, distributed machine learning to holonic systems, cooperative enterprise modeling, system integration, and autonomous logistics processes are surveyed. A special emphasis is put on the theoretical developments and industrial applications of Robustly Feasible Model Predictive Control (RFMPC). Two case studies are also discussed: (i) a holonic, PROSA-based approach to generate short-term forecasts for an additive manufacturing system by means of a delegate multi-agent system (D-MAS); and (ii) an application of distributed RFMPC to a drinking water distribution system.