Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.

  

Marcello Colombino

Marcello Colombino
Dr. sc. ETH Zürich, Postdoc


Automatic Control Laboratory
Swiss Federal Institute of Technology
Physikstrasse 3, ETL K 26
CH-8092

Phone: +41 44 632 4923
Email: mcolombi@control.ee.ethz.ch

In February 2018, I will join the National Renewable Energy Laboratory in Golden, CO, USA. I am always interested in motivated students for master thesis or summer internship opportunities in the USA in the field of control and optimization for power systems.

In 2017, I joined the group of Prof. Florian Dörfler to work on on the European Project Migrate, studying the effect of massive integration of power electronic devices into the grid. I studied new control strategies for power inverters in order to guarantee the stability and performance of the power grid without rotational inertia.

In 2016, I earned my Ph.D. in the Automatic Control Laboratory of ETH Zurich, Switzerland, under the supervision of Prof. Roy S. Smith and in 2012 I completed my MEng in Biomedical Engineering from Imperial College London.

On a lighter note, in April 2016, I was part of a ski-mountaineering expedition in the Indian Himalaya. Check out our blog!

Selected publications

For a complete list of my publications, see my Google Scholar page
Google logo

Decentralized control of power inverters

In the recent submission to IEEE Transaction on Automatic Control [CGB+17] we explore a new approach to controlling networks of inverters to achieve synchronization of phase angles, frequencies, and ensure convergence to a desired voltage magnitude. We design a synchronizing vector field for a network of interconnected inverters which induces consensus-like dynamics and admits a fully decentralized implementation. We show that the combination of the synchronizing feedback and a simple voltage control law ensures synchronization of the inverters phase angles and frequencies, as well as convergence of the voltage magnitudes from almost all initial conditions. Furthermore, we show that the controller exhibits a droop-like behavior around the standard operating point thus making it backwards-compatible with the existing power grid. The preliminary results were presented at CDC in Melbourne [CGD17].

[CGB+17] Colombino, M., Gross, D., Brouillon, J.S. & Dörfler, F.
Global phase and magnitude synchronization of coupled oscillators with application to the control of grid-forming power inverters.
Submitted to Automatic Control, IEEE Transactions on., 2017.
[CGD17] Colombino, M., Gross, D. & Dörfler, F.
Global phase and voltage synchronization for power inverters: a decentralized consensus-inspired approach.
In Conference on Decision and Control, 2017.

Together with our Master student Jean-Sebastien we have extended the analysis of our synchronizing controller by taking into account the full dynamics of the transmission lines. Interesting counterintuitive results will be out soon. Stay tuned!

Our Master student Irina Subotic is working on designing local inner control loops for power inverters that provide global system-level stability gurantees. She will join me at NREL for three months of experiments in collaboration with Brian Johnson.

Robust and decentralized control of Positive Systems

During my PhD [C16] I focused mainly on the study of robust and decentralized control for positive systems. Positive systems arise in multiple application fields where the state variables are inherently nonnegative. In [CS16] we study the problem of assessing the robust stability of uncertain positive systems. We provide convex necessary and sufficient conditions for the robust stability of linear positively dominated systems which are a strict superclass of positive systems. In particular, we show that the structured singular value is always equal to its convex upper bound for nonnegative matrices and we use this result to derive necessary and sufficient Linear Matrix Inequality (LMI) conditions for robust stability that involve only the system's static gain.

In [DCJ17] and [DCJ16] we study a class of structured optimal control problems for positive systems in which the design variable modifies the main diagonal of the dynamic matrix. For this class of systems, we establish convexity of both the H-2 and H-infinity optimal control formulations. In contrast to previous approaches, our formulation allows for arbitrary convex constraints and regularization of the design parameter. We provide expressions for the gradient and subgradient of the H-2 and H-infinity norms and establish graph-theoretic conditions under which the H-infinity norm is continuously differentiable. Finally, we develop a customized proximal algorithm for computing the solution to the regularized optimal control problems and apply our results for HIV combination drug therapy design.

[C16] Colombino, M.
Robust and Decentralized Control of Positive Systems: a Convex Approach.
ETH Zurich, 2016. [doi: 10.3929/ethz-a-010736004]
[CS16] Colombino, M. & Smith, R.S.
A Convex Characterization of Robust Stability for Positive and Positively Dominated Linear Systems.
Automatic Control, IEEE Transactions on, 61(7):1965-1971, 2016. [doi: 10.1109/TAC.2015.2480549]
[DCJ17] Dhingra, N.K., Colombino, M. & Jovanović, M.R.
Structured decentralized control of positive systems with applications to combination drug therapy and leader selection in directed networks.
IEEE Transactions on the Control of Network Systems, Provisionally accepted, 2017.
[DCJ16] Dhingra, N.K., Colombino, M. & Jovanovic, M.
On the Convexity of a Class of Structured Optimal Control Problems for Positive Systems.
In Proceedings of the 2016 European Control Conference, 2016.

Structured Dynamic Games

In [CSS17] we formulate a two-team linear quadratic stochastic dynamic game featuring two opposing teams each with decentralized information structures. We introduce the concept of mutual quadratic invariance (MQI), which, analogously to quadratic invariance in (single team) decentralized control, defines a class of interacting information structures for the two teams under which optimal linear feedback control strategies are easy to compute. We show that, for zero-sum two-team dynamic games, structured state feedback Nash (saddle-point) equilibrium strategies can be computed from equivalent structured disturbance feedforward saddle point equilibrium strategies. However, for nonzero-sum games we show via a counterexample that a similar equivalence fails to hold. The results are illustrated with a simple yet rich numerical example that illustrates the importance of the information structure for dynamic games.

[CSS17] Colombino, M., Smith, R.S. & Summers, T.H.
Mutually Quadratically Invariant Information Structures in Two-Team Stochastic Dynamic Games.
Automatic Control, IEEE Transactions on, in press, 2017.

Aggregative Games/Mean Field Control

In [GPC+16] we consider decentralized control and optimization methodologies for large populations of systems, consisting of several agents with different individual behaviors, constraints and interests, and influenced by the aggregate behavior of the overall population. For such large-scale systems, the theory of aggregative and mean field games has been established and successfully applied in various scientific disciplines. While the existing literature addresses the case of unconstrained agents, we formulate deterministic mean field control problems in the presence of heterogeneous convex constraints for the individual agents, for instance arising from agents with linear dynamics subject to convex state and control constraints. We propose several model-free feedback iterations to compute in a decentralized fashion a mean field Nash equilibrium in the limit of infinite population size. We apply our methods to the constrained linear quadratic deterministic mean field control problem.

[GPC+16] Grammatico, S., Parise, F., Colombino, M. & Lygeros, J.
Decentralized convergence to Nash equilibria in constrained mean field control.
Automatic Control, IEEE Transactions on, 2016.

Teaching

I am no longer teaching at ETH. If you are interested in a master thesis in collaboration with NREL, Colorado, USA in the field of control and optimization for power systems please contact me or Prof. Dorfler. We are always looking for motivated students.

Master Thesis and Semester projects

Open projects