Automatic Control develops methods and tools for the modelling of dynamic systems (physical, chemical, biological, economic, social) for their analysis and for their control, in order to perform tasks and/or optimize criteria. Automatic Control makes use of mathematics, signal processing, computer science and knowledge on various fields of application. This discipline is essential for analysis, design and simulation, optimize, validate and verify technological and socio-technological systems that are to become more and more interconnected in the next decade. It currently focuses, among other topics, on the treatment of massive volume of data and information, and on the new forms of synergy between humans and technological systems. In addition, these complex systems will have to meet more and more requirements on performance, reliability and energy efficiency.
The Industrial Engineering community addresses issues related to products, processes, organizations and networks of organizations, at all stages of their life cycle: design, management, improvement and end of life (including the preservation of knowledge in the very long term). In that purpose, we consider models, approaches and tools from automatic control (modelling, system management), IT (artificial intelligence, computer engineering, information technology, etc.), mechanical engineering (product design and manufacturing processes) or operational research (planning, scheduling, optimisation). Being of multidisciplinary nature, this domain is often addressed in collaboration with other research communities, such as economics and management sciences and the humanities (business sociology, law, etc.).