M09 – PARIS‐SACLAY 29/02/2016 ‐ 04/03/2016

Randomized algorithms for systems, control and networks

Roberto Tempo
CNR-IEIIT, Politecnico di Torino, Italy


In this course, we provide a perspective of the research area of randomization for systems, control and networks. In particular, we study several topics which are of interest when dealing with control of uncertain systems and networks described by graphs.

Randomization is a key tool to handle uncertain systems and  control problems which can be solved only approximately due to partial or contaminated data, or because only local information about the network is available. Various techniques are developed in the course to construct synchronous and asynchronous sequential algorithms for analysis and design. Convergence and optimality properties of these algorithms  are analyzed.

We also discuss several applications, which include stochastic model predictive control, anti-windup compensation, the PageRank computation, control design of unmanned aerial vehicles and clock synchronization of wireless networks. The course is based on the book by R. Tempo, G. Calafiore, F. Dabbene, “Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications,” 2nd edition, Springer, London, 2013.


-Uncertain systems, networks and graphs
-Monte Carlo and Las Vegas algorithms
-Random sampling techniques
-Probabilistic methods for control design
-Distributed randomized algorithms
-Systems and control applications