Title of the talk: Towards a Rigorous Framework for MBSE and Applications
Affiliation: Lockheed Martin Chair in Systems Engineering Institute for Systems Research, University of Maryland College Park and Tage Erlander Guest Professor, ACCESS Center, KTH, and Hans Fischer Senior Fellow, IAS-TUM
Abstract: Advances in Information Technology have enabled the design of complex engineered systems, with large number of heterogeneous components and capable of multiple complex functions, leading to the ubiquitous cyber-physical systems (CPS). These advances have at the same time increased the capabilities of such systems and have increased their complexity to such an extent that systematic design towards predictable performance is extremely challenging, if not infeasible with current methodologies and tools. We first describe a rigorous framework we are developing for model-based systems engineering (MBSE), a system level design methodology that addresses these challenges, which also incorporates manufacturing, operation and life cycle considerations. We describe the three fundamental components for MBSE within our framework: (a) An integrated systems modeling hub built around SysML, employing meta-modeling methods and environments and easy interfaces with a variety of domain specific design methods and tools; (b) Linking this modeling hub with tradeoff analysis tools for design space exploration, employing linkage with the parametric and requirements diagrams of SysML, and integrated methods and tools from multi-criteria mixed (integer and numerical variables and metrics) optimization and constrained based reasoning; (c) Representation and management of requirements, employing initial efforts towards an integration of methods and tools from model checking, contract based design and automatic theorem proving, and including finite time temporal logic specifications for system behavior. We describe our results for conquering and managing the complexity of queries in design, manufacturing and operational space exploration. We provide a short description of the new fundamental challenges faced when incorporating humans as elements of such complex systems, a subject of rapidly increasing importance in view of the “networked society” and the “interconnected coevolving sociotechnical networks” paradigms. We next describe applications of the framework to several important current technological problems (several major domains of CPS): power grids, automotive, aerospace, energy efficient buildings, sensor and communication networks, smart manufacturing, robotics and UAVs, health care, cyber-security. We close with a description of what is still lacking, research challenges and future promising research directions.
Short Bio: Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens, Greece, 1970; M.S., Ph.D. in Applied Mathematics from Harvard University 1971, 1973. Since 1973, faculty member in the Electrical and Computer Engineering Department, and in the Applied Mathematics, Statistics and Scientific Computation Program, at the University of Maryland College Park. Since 2000, faculty member in the Fischell Department of Bioengineering. Since 2014, faculty member in the Mechanical Engineering Department. Founding Director of the Institute for Systems Research (ISR), 1985 to 1991. Since 1991, Founding Director of the Maryland Center for Hybrid Networks (HYNET). Since 2013, Guest Professor at the Royal Institute of Technology (KTH), Sweden. IEEE Life Fellow, SIAM Fellow, AAAS Fellow, NAI Fellow, and a Foreign Member of the Royal Swedish Academy of Engineering Sciences (IVA). Received the 1980 George Axelby Prize from the IEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE Communications Society, the 2014 Tage Erlander Guest Professorship from the Swedish Research Council, and a three year (2014-2017) Senior Hans Fischer Fellowship from the Institute for Advanced Study of the Technical University of Munich, Germany. Professor Baras' research interests include systems and control, optimization, communication networks, signal processing and understanding, robotics, computing systems and networks, network security and trust, and model-based systems engineering.
