18-777 Complex Large-Scale Dynamic Systems
12 units, Carnegie Mellon University
This course is motivated by the evergrowing complexity of manmade dynamic systems and the need for flexible monitoring, operations and design techniques for such systems. Of particular interest are systematic modelbased methods for relating the key reallife problems for such systems and the stateoftheart techniques for largescale dynamic systems. Examples of such reallife complex systems are critical manmade infrastructure systems electric power systems, gas networks, transport industries, data networks, and their interdependencies as well as largescale systems on chips. In this course we will first review the traditional largescale methods for model simplification aggregation, time scale separation of subprocesses and singular perturbation techniques to account for these, stability analysis, and estimation and control. In the second, novel part of this course, we recognize the highly interactive nature of the evolving complex systems, in which much monitoring, data gathering, and decision making is made at the lower, physical levels of the system, and some coordination exists at the higher system level at which physical layers interact. Several conceptual challenges are posed for minimal coordination of such decision makers under high uncertainties, in order to have predictable performance. These concepts will be illustrated using the same manmade network systems of interest introduced at the beginning of the course. Requirements Some background in dynamic systems is highly desirable. Students interested in largescale reallife complex systems, their relation to the stateoftheart methods available and new research challenges will gain from taking this course. 4 hrs lec. Prerequisites senior or graduate standing.
Prerequisites: none listed
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