The course provides the skills and knowledge for the advanced control of complex systems, which may consist of multiple agents, such as multiple robotic platforms. It will present distributed control methodologies for multi-agent systems, where each robot determines its control actions based on local information. To this end, the course will cover the fundamentals of algebraic graph theory and their application to coordination problems, such as consensus, formation control, and distributed optimization.
The topic of predictive control will also be addressed, starting from the foundations of optimal control. The course will introduce the basics of formulating and solving Model Predictive Control (MPC) problems applied to complex, multivariable dynamic processes. Furthermore, the main MPC formulations will be analyzed, including centralized and distributed approaches, with a particular focus on systems composed of multiple interacting subsystems subject to constraints.
The topic of predictive control will also be addressed, starting from the foundations of optimal control. The course will introduce the basics of formulating and solving Model Predictive Control (MPC) problems applied to complex, multivariable dynamic processes. Furthermore, the main MPC formulations will be analyzed, including centralized and distributed approaches, with a particular focus on systems composed of multiple interacting subsystems subject to constraints.
scheda docente
materiale didattico
Graph theory and algebraic graph theory
Consensus protocols with different graphs
Formation control
Control of robot swarms and further coordination problems
Introduction to Model Predictive Control and mathematical fundamentals
Formulation of the MPC Problem
Stability of MPC
MPC for Multi-agent Systems
- Camacho, E. F., & Bordons, C., Model Predictive control, Springer, ISBN: 978-1-85233-694-3, 2013.
- Lecture notes
Programma
Introduction to multi-agent systemsGraph theory and algebraic graph theory
Consensus protocols with different graphs
Formation control
Control of robot swarms and further coordination problems
Introduction to Model Predictive Control and mathematical fundamentals
Formulation of the MPC Problem
Stability of MPC
MPC for Multi-agent Systems
Testi Adottati
- F. Bullo, Lectures on Network Systems, CreateSpace Independent Publishing Platform, ISBN 978-1986425643, 2022- Camacho, E. F., & Bordons, C., Model Predictive control, Springer, ISBN: 978-1-85233-694-3, 2013.
- Lecture notes
Bibliografia Di Riferimento
- Veysel Gazi and Kevin Passino. 2011. Swarm Stability and Optimization. Springer Publishing Company, Incorporated. ISBN 978-3642422706 - F. Bullo, J. Cortes, and S. Martinez, Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms, Princeton University Press, Princeton, NJ, USA, 2009. - M. Mesbahi and M. Egerstedt, Graph Theoretic Methods for Multiagent Networks, Princeton University Press, Princeton, NJ, 2010. - Maciejowski, J., Predictive Control with Constraints, Pearson Education POD, 2002. - Rossiter, J. A., Model-Based Predictive Control: A Practical Approach, CRC Press, 2003. - Maestre, J. M., & Negenborn, R. R. (Eds.). (2014). Distributed model predictive control made easy (Vol. 69). Dordrecht, Netherlands: Springer.Modalità Frequenza
Attendance is strongly recommended given the practical nature of the course.Modalità Valutazione
The exam consists of an oral test to discuss the theoretical aspects of the course and a project to explore the practical aspects of the course.
scheda docente
materiale didattico
- Graph theory and algebraic graph theory
- Consensus protocols with different graphs
- Formation control
- Control of robot swarms and further coordination problems
- Introduction to Model Predictive Control and mathematical fundamentals
- Formulation of the MPC Problem
- Stability of MPC
- MPC for Multi-agent Systems
- Camacho, E. F., & Bordons, C., Model Predictive control, Springer, ISBN: 978-1-85233-694-3, 2013.
- Lecture notes
Programma
- Introduction to multi-agent systems- Graph theory and algebraic graph theory
- Consensus protocols with different graphs
- Formation control
- Control of robot swarms and further coordination problems
- Introduction to Model Predictive Control and mathematical fundamentals
- Formulation of the MPC Problem
- Stability of MPC
- MPC for Multi-agent Systems
Testi Adottati
- M. Mesbahi and M. Egerstedt, Graph Theoretic Methods for Multiagent Networks, Princeton University Press, Princeton, NJ, 2010.- Camacho, E. F., & Bordons, C., Model Predictive control, Springer, ISBN: 978-1-85233-694-3, 2013.
- Lecture notes
Bibliografia Di Riferimento
- Veysel Gazi and Kevin Passino. 2011. Swarm Stability and Optimization. Springer Publishing Company, Incorporated. ISBN 978-3642422706 - F. Bullo, J. Cortes, and S. Martinez, Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms, Princeton University Press, Princeton, NJ, USA, 2009. - F. Bullo, J. Cortes, and S. Martinez, Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms, Princeton University Press, Princeton, NJ, USA, 2009. - Maciejowski, J., Predictive Control with Constraints, Pearson Education POD, 2002. - Rossiter, J. A., Model-Based Predictive Control: A Practical Approach, CRC Press, 2003. - Maestre, J. M., & Negenborn, R. R. (Eds.). (2014). Distributed model predictive control made easy (Vol. 69). Dordrecht, Netherlands: Springer.Modalità Frequenza
Attendance is strongly recommended given the practical nature of the course.Modalità Valutazione
The exam consists of an oral test to discuss the theoretical aspects of the course and a project to explore the practical aspects of the course.