The goal of the research projects in “networked dynamical systems” and “adaptive control in networked control systems” was to understand mechanisms that drive global dynamic behavior in complex systems and develop methods for technological conversion of achieved theoretical results. Electric infrastructures are chosen as application due to its significance in science and technology with an impetus for societal changes and vice versa.
Theory of large-scale interconnected systems
Global dynamic behavior is characterized in a modus ponens through local dynamical systems that interact with each other in a certain way: a graph structure assigns pair-wise relations, and communication allows for information exchange. Specific performance criteria for operation in the context of robustness and efficiency require specific laws for local controls and local-to-local interactions. Understanding complexity in this context means to understand how global behavior as operational mode of a network can be shaped by intrinsically enhancing the collective's interaction in a desired direction: how does a network of dynamical systems process information and how does this processed quantity lead to desired functionality?!
Control, communication & optimization
In a systems and control context these issues are handled in the emerging field of distributed control and cyber-physical adaptive control systems: a “cyber-structure” monitors, predicts and manages a networks function in parallel to local operation. Hence, “cyber-physical” systems require methods for the co-design of control and communication architectures, which combine adaptive switching controllers with a multi-modal real-time system.
Dynamics of energy markets
On the other hand, a large portion of uncertainty comes from the interaction of technology (smart grid as cyber-physical infrastructure) with consumers. Demand and supply of electric power need to be balanced in real-time, and additionally, the production and transport of electrical energy shall be accomplished in an economically efficient way. Energy markets are meant to handle organizational issues on this level, whereat new problems arise: Pricing mechanism that couple demand and supply via generation and transportation costs are seen to produce dynamics in energy markets in terms of feedback-loops. Pricing schemes as control laws have to be designed adequate to produce well-behaved closed-loop systems. Estimation techniques and performance-oriented control play a crucial role in diminishing uncertainty and volatility in pricing and power generation.
Prof. Anuradha Annaswamy is the Director of the Active-Adaptive Control Laboratory and a Senior Research Scientist in the Department of Mechanical Engineering at MIT where her group members are developing novel control methods for high performance in flight, propulsion, and automotive systems that have to function in uncertain environments. As a Hans Fischer Senior Fellow of TUM-IAS, Annaswamy focused on developing a distributed adaptive control theory for large-scale networked dynamic systems subject to uncertainties. Technology advances, combined with increasingly stringent performance specifications as well as considerations of cost, size, and reliability, are fueling an increasing interest in the analysis and synthesis of networked control systems and are raising fundamentally new questions in control, communications, and information processing. Annaswamy’s goal is to develop the blueprint for such a system as well as its cognitive ability to self-adapt and learn when subjected to different uncertainties. All of her research activities were carried out in collaboration with the Network Control Systems group in the Innstitute of Automatic Control Egineering at TUM.
Dr. Dragan Obradovic is a Rudolf Diesel Industry Fellow of the TUM Institute for Advanced Study. He received his B.E. and M.E. degrees in Mechanical Engineering in 1980 and 1985 from the University of Belgrade, Serbia, the latter parallel to holding a Research Engineer position in the Institute Mihailo Pupin. In 1990 he received the Ph.D. degree in Mechanical Engineering from the Massachusetts Institute of Technology, Cambridge, USA. After finishing his PhD, he stayed at MIT until the end of 1991 in the position of a Postdoctoral Fellow at the Laboratory for Information and Decision Systems (LIDS).
Since 1992, Obradovic has been with Siemens Corporate Technology, Information and Communications, in Munich, Germany where he currently holds a position of Senior Research Scientist. In addition, since 2001 Obradovic has been teaching as an Industrial Lecturer in the international “Masters of Science in Communication Engineering (MSCE)” program within the EE Department at Technical University Munich.Obradovic’ research interests involve, among others, machine learning applications to signal processing, networked control systems, clock synchronization in automation systems, and control of wind turbines and of smart grid.
TUM-IAS funded doctoral candidates:
Arman Kiani (PhD in 2012)
Herbert Mangesius, Automatic Control Engineering
Harald Voit (PhD in 2012)
- An Arbitrated Networked Control Systems Approach to Cyber-Physical Systems. Dissertation, 2013 mehr…
- Quasi-Stationarity of Electric Power Grid Dynamics Based on a Spatially Embedded Kuramoto Model. American Control Conference, 2012 mehr…
- On Signaling and Invariance Principles Determining Global Solution Properties of Oscillator Networks and its Approximations Illustrated on Electric Power Grid Dynamics. American Control Conference, 2012 mehr…
- Precise clock synchronisation for industrial and other networked applications. LCCC workshop on Information and Control in Networks, 2012 mehr…
- Adaptive Switching Controllers for Systems with Hybrid Communication Protocols. American Control Conference, 2012 mehr…
- Synchronization Performance of the Precision Time Protocol in Industrial Automation Networks. IEEE Trans. Instrum. Meas. 58 (6), 2009, 1849-1857 mehr…