ACCESS PhD Course on Networked and Multi-Agent Control Systems, FEL3330, HT16

Credits: The course is worth 7.5 credits. Grading is based on P/F system.

 

PhD Course category: Specialized.

 

Course responsible: Dimos Dimarogonas, dimos@kth.se.

 

Lecturers: Dimos Dimarogonas, Dimitris Boskos.

 

Abstract

 

Recent technological advances in computational and communication resources have facilitated the control of multi-agent systems. Such systems are comprised of a large number of entities (“agents”) that aim at achieving a global task. Distributed control designs are preferable, since they provide among others scalability, reduce of computational load and fault compensation. Moreover they are natural realizations of the limitations in communication, networking, and sensing capabilities which are inherent in multi-agent systems.

Multi-agent systems have a broad range of modern applications such as multi-robot and multi-vehicle coordination, control of sensor networks, air traffic management systems, unmanned vehicles, energy systems and logistics, just to name a few. This course will review the fundamental tools, problems and state of the art in the modeling and control of networked multi-agent systems. Moreover it will indicate possible future research directions.

 

Keywords

 

Multi-agent systems, multi-robot systems, networked systems, distributed control under limited communication and sensing, formation control, sensor networks.

 

Learning outcomes

 

After the course, the student should be able to:

·        know the essential theoretical tools to cope with Networked and Multi-Agent Systems

·        know the established problems and results in the area

·        apply the theoretical tools to problems in the area

·        contribute to the research frontier in the area

 

Course main content

 

A preliminary structure and exact dates are given below. Reading material for each lecture will be updated as the course evolves.

 

Lecture 1:  Introduction, motivation, applications, logistics, etc.  (August 31, Q11, 3-5 pm)

Reading material for lecture 1:

  1. Chapter 1 and Appendix from Graph Theoretic Methods in Multi-Agent Networks, by M. Mesbahi and M. Egerstedt, Princeton University Press, 2010 (thereafter refered to as “Mesbahi and Egerstedt”).
  2. For a thorough overview of stability of switched systems, refer to D. Liberzon, Switching in Systems and Control, Birkhauser, 2003., Part II.

 

Lecture 2:  Graphs and Matrices.   (September 5, Q11, 1-3 pm)

Reading material for lecture 2:

  1. Chapter 2 from Mesbahi and Egerstedt.
  2. Lecture notes.

 

Lecture 3: Agreement protocols 1.  (September 7, Q11, 3-5 pm)

Reading material for lecture 3:

  1. Chapters 3.1, 3.2 from Mesbahi and Egerstedt.
  2. R. Olfati-Saber and R. M. Murray. "Consensus Problems in Networks of Agents with Switching Topology and Time-Delays," IEEE Trans. on Automatic Control, vol. 49(9), Sep., 2004.
  3. Wei Ren and Randal W. Beard, "Consensus seeking in multiagent systems under dynamically changing interaction topologies," IEEE Transactions on Automatic Control, Vol. 50, No. 5, May 2005,  pp. 655-661.

 

Lecture 4: Agreement protocols 2.  (September 12, Q13, 3-5 pm)

Reading material for lecture 4:

  1. Chapters 4.1, 4.2, 4.3 from Mesbahi and Egerstedt.
  2. D.V. Dimarogonas and K.H. Johansson, “Stability analysis for multi-agent systems using the incidence matrix: quantized communication and formation control”, Automatica,  46: 4, pp. 695-700, April 2010.

 

Lecture 5: Formation control 1: position based formations, formation infeasibility, flocking.    (September 15, Q13, 1-3 pm)

Reading material for lecture 5:

  1. Chapters 6.2, 6.4 from Mesbahi and Egerstedt.
  2. D.V. Dimarogonas and K.H. Johansson, “Stability analysis for multi-agent systems using the incidence matrix: quantized communication and formation control”, Automatica,  46: 4, pp. 695-700, April 2010.

3.       P. 2648-2651 from D.V. Dimarogonas and K.J. Kyriakopoulos, “A connection between formation infeasibility and velocity alignment in kinematic multi-agent systems”, Automatica, Vol. 44, No. 10, pp. 2648-2654, October 2008.

4.       Herbert G. Tanner, Ali Jadbabaie and George J. Pappas, “Stable Flocking of Mobile Agents, Part I: Fixed Topology”  IEEE Conference on Decision and Control, 2003, pp. 2010-2015.

 

Lecture 6: CANCELLED   (September 20, Q13, 3-5 pm)

Lecture 7:  Sensing Constraints 1: connectivity, connectivity maintenance. Given by Dimitris Boskos (September 22, Q11, 3-5 pm)

Reading material for lecture 7:

  1. Chapters 7.1-7.3 from Mesbahi and Egerstedt.

2.       Meng Ji and Magnus Egerstedt, “Distributed Coordination Control of Multiagent Systems while Preserving Connectedness” IEEE Transactions on Robotics, Vol. 23, No. 4, pp. 693-703, Aug. 2007.

3.       Dimitris Boskos and Dimos V. Dimarogonas, “Robust Connectivity Analysis for Multi-Agent Systems”, 54th IEEE Conference on Decision and Control, Osaka, Japan, pp. 6767-6772, December 2015.

Lecture 8:  Formation control 2: distance based formations, rigidity.   (September 27, Q13, 3-5 pm)

Reading material for lecture 8:

  1. Chapters 6.1, 6.3 from Mesbahi and Egerstedt.

2.       Herbert G. Tanner, On the Controllability of Nearest Neighbor Interconnections.  IEEE Conference on Decision and Control, 2004, pp. 2010-2015.

3.       Laura Krick, Mireille E. Broucke, and Bruce A. Francis, “Stabilization of Infinitesimally Rigid Formations of Multi-Robot Networks”, IEEE CDC 2008.

4.       BRIAN D. O. ANDERSON , IMAN SHAMES, GUOQIANG MAO, AND BARIS FIDAN, “FORMAL THEORY OF NOISY SENSOR NETWORK LOCALIZATION”, SIAM J. DISCRETE MATH., Vol. 24, No. 2, pp. 684–698.

Lecture 9:  Sensing Constraints 2: Swarming-sensor networks.   (September 29, Q11, 3-5 pm)

Reading material for lecture 9:

  1. Dimos V. Dimarogonas and Kostas J. Kyriakopoulos, “Inverse Agreement Protocols with Application to Distributed Multi-agent Dispersion”, IEEE Transactions on Automatic Control, Vol. 54, No. 3, pp. 657-663, March 2009.
  2. Dimos V. Dimarogonas and Kostas J. Kyriakopoulos, "Connectedness Preserving Distributed Swarm Aggregation for Multiple Kinematic Robots", IEEE Transactions on Robotics, Vol. 24, No. 5, pp. 1213-1223, October 2008.

 

Lecture 10:  Communication constraints: quantization, event-triggered sampling and control.    (October 3, B24, 3-5 pm)

Reading material for lecture 10:

1.       Meng Guo and Dimos V. Dimarogonas, Consensus with Quantized Relative State Measurements, Automatica, Vol. 49, No. 8, pp. 2531–2537, August 2013.

2.       Georg S. Seyboth, Dimos V. Dimarogonas and Karl H. Johansson, Event-based Broadcasting for Multi-agent Average Consensus, Automatica, Vol. 49, No. 1, pp. 245-252, January 2013.

 

Lecture 11:   Guest lecture: Guarding, Searching and Pursuing Evaders using Multiagent Systems. Prof. Petter Ögren.   (October 5,  Q11, 10-12 am)

 

Reading material for lecture 11:

1.       Frank Hoffmann, Michael Kaufmann and Klaus Kriegel, ”The Art Gallery Theorem For Polygons With Holes”, 32nd Annual Symposium on  Foundations of Computer Science, 1991.

2.       Noa Agmon, Noam Hazon and Gal A Kaminka. Constructing spanning trees for efficient multirobot coverage. In ICRA '06: Proceedings of IEEE International Conference on Robotics and Automation, pages 3462-3468, 2006.

3.       Volkan Isler, Sampath Kannan, and Sanjeev Khanna, ”Randomized Pursuit–Evasion in a Polygonal Environment”, IEEE Trans. On Robotics, VOL. 21, NO. 5, OCTOBER 2005.

4.       J. Cortés, S. Martínez, T. Karatas, F. Bullo, Coverage control for mobile sensing networks, IEEE Transactions on Robotics and Automation, 20 (2), 243-255, 2004.

 

Lecture 12:  Project presentations (tentative).    (October 17, Q11, 10-12 am)

Course disposition

 

Lectures, course literature.

 

Prerequisites

 

Basic courses on Automatic Control, Linear Algebra. At least one advance course in automatic control will be of help, but not compulsory.

 

Requirements for final grade

 

Passing Grade based on homework and final project/take-home exam.

 

Course literature

 

The course will be primarily based on the book

 

Graph Theoretic Methods in Multi-Agent Networks, by M. Mesbahi and M. Egerstedt, Princeton University Press, 2010.

 

as well as lecture slides and suggested reading for the topic of each lecture.

 

Relevant supplementary textbooks are

 

Algebraic Graph Theory, by C. Godsil and G. Royle, Springer, 2001.

 

Distributed Control of Robotic Networks, by F. Bullo, J. Cortes, and S. Martinez, Princeton, 2009.

 

Distributed Consensus in Multi-vehicle Cooperative Control, by Wei Ren, Randal W. Beard, Communications and Control Engineering Series, Springer-Verlag, London, 2008 (ISBN: 978-1-84800-014-8).