September 21-23, 2017 Yildiz Technical University, Davutpasa Campus
Institute for Systems Theory and Automatic Control
Department of Mechanical Engineering
University of Stuttgart, Germany
With the vision of the smart factory of the future, termed Industry 4.0 in Germany, the manufacturing industries are currently undergoing a fundamental new orientation on the basis of the Cyber-Physical Systems and Internet of Things and Services paradigms. All parts along the manufacturing chain are nowadays equipped with embedded computing, communication and networking capabilities and are expected to interact in an optimal way towards the goal of an energy and resource efficient, save and reliable production process. Through decentralized optimal decision-making and an appropriate communication among the networked individual parts, the whole production process of the future is expected to operate optimally. In this presentation the challenges and opportunities of Industry 4.0 for the field of automatic control are discussed. We will in particular investigate the potential impact of networked and optimization-based control for the fourth industrial revolution and will argue that some new developments in the control field, especially connected to distributed economic model predictive control, appear to be ideally suited to have a potential impact in the new Industry 4.0 environment.
Center for Research on Complex Automated Systems (CASY)
Department of Electrical, Electronic and Information Engineering (DEI)
University of Bologna, Italy
This talk deals with the problem of output regulation for nonlinear systems. In the first part of the talk we present key notions and tools governing the design of internal model-based regulators for nonlinear systems. We overview the main results presented in literature in the last decade for single-input single-error systems with a special emphasis toward high gain-based methods and to recently introduced approaches based on identification. Then, in the second part of the talk, the problem in question is approached for multivariable systems. The main goal is to show the main obstructions that prevent one to extend straightforwardly results reviewed in the first part and why design principles that hold for linear multivariable systems have not a direct nonlinear counterpart. Preliminary results of robust multivariable output regulation for specific classes of nonlinear systems are finally presented.