Modeling and Control of Complex Systems

Our ability to interact with the environment is now spanning an unprecedented range of scales. At the one extreme is the ability to manipulate individual atoms over a substrate and gene expression in cells. At the other extreme, human engineered systems, such as the internet and power grids, span large portions of the globe. Remarkably, a consistent picture is emerging across these scales, pointing out to a suit of characteristics and challenges, common to much of these developments, and the resolution of these challenges is essential to unlock the full promise of the new technologies. These include the need to interact with distributed, multi-scale processes and phenomena, the profusion of available data streams, and an unmet need to reliably extract and exploit structure and meaning, from such data.

Despite a considerable recent impetus and substantial achievements in the study of complex systems by industry and in academe, much of the obstacles mentioned above are yet to be systematically unresolved. The modeling and control group at CDSP aims to exploit the enormous potential of linear and nonlinear, robust dynamical systems tools, as common, efficient and effective means for complexity resolution, mitigation and management, across a wide, family of multi-scale, distributed problems. Examples of current activities include:

Topical areas:

• modeling and system identification
• model reduction in linear and nonlinear systems
• robust linear and nonlinear control design
• control and estimation in delay systems
• application areas
• computer vision and video based tracking
• modeling and control of fluid dynamical systems
• biomedical dynamic imaging
• integrity analysis of civil structures
• application of multi-scale modeling in physics

Current group members include: Dennis Bernal, Bahram Shafai, Mario Sznaier, Gilead Tadmor