From the 2000s, a number of research works have been devoted to control of networked systems, in particular, control of multi-agent systems wherein the goal is to present inter-agent local interaction laws leading to desirable global behavior. Currently, it is not too much to say that knowledge on this theory is indispensable for doing advanced research. The network control systems include applications such as sensor networks, smart energy management systems, intelligent transportation systems and system biology, which are all relevant to the present social issues. This course starts with introduction to graph theory which was newly brought to control engineering by control of network systems. Students then learn the most fundamental control problem of multi-agent systems, namely, consensus control. Moreover, this course also addresses advanced issues such as synchronization control, coverage control and cooperative distributed optimization.
This course treats network control systems and educates the concept, problem formulations, solutions and background theory. Through this course, students would know several typical control problems, applications and fundamental theory of network control systems. This would help students have access to the state-of-the-art in systems and control, and to produce novel research outcomes. Also, students will acquire several background theories such as graph theory, Lyapunov theory and optimization theory.
Network Control Systems, Multi-agent Systems, Graph Theory, Consensus Control, Synchronization Control, Coverage Control, Cooperative Distributed Optimization, Noncooperative control, Game theory
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
1) At the beginning of each class, solutions to exercise problems assigned in the previous class are reviewed.
2) Attendance is taken in every class.
3) Students must familiarize the contents assigned in the previous class before coming to the class.
Course schedule | Required learning | |
---|---|---|
Class 1 | Network Control Systems | Students must make sure they understand what significance the course holds for them by checking their learning portfolio. Peruse Chapter 1 of the course textbook |
Class 2 | Graph Theory | Peruse Chapter 2 of the course textbook |
Class 3 | Continuous-Time Consensus Control | Peruse Section 3.1 and 3.2 of the course textbook. The homework must be handed in next class. |
Class 4 | Discrete-Time Consensus Control | Peruse Section 3.3 and 3.4 of the course textbook The homework must be handed in next class. |
Class 5 | Synchronization Control | The homework must be handed in next class. |
Class 6 | Coverage Control | Peruse Chapter 4 of the course textbook. The homework must be handed in next class. |
Class 7 | Cooperative Distributed Optimization | Peruse Chapter 5 of the course textbook The homework must be handed in next class. |
Class 8 | Course Summary |
M. Mesbahi and M. Egerstedt, Graph Theoretic Methods in Multiagent Networks,
Princeton Series in Applied Mathematics, Princeton University Press ISBN: 9781400835355
S. Azuma and M. Nagahara (eds.), Control of Multi-agent Systems ISBN: 9784339033229
Students will be assessed on their understanding of the concept of network control systems, theory, solution and their applications. The course scores are based on exercise problems.
Students must have successfully completed SCE.C.202, SCE.C.302, SCE.C.402, SCE.C.531, SCE.C.501, and SCE.C.502 or have equivalent knowledge.
Hayakawa: tel 03-5734-2762, email hayakawa[at]sc.e.titech.ac.jp
Hatanaka: tel 03-5734-3316, email hatanaka[at]ctrl.titech.ac.jp