Andrea Alessandretti

Postdoctoral researcher

Dept. of Electrical and Computer Engineering (DEEC)
Faculty of Engineering, University of Porto (FEUP)
Rua Dr. Roberto Frias, s/n
4200-465 Porto, PORTUGAL
E-mail: andrea.alessandretti@fe.up.pt
FEUP

Biographical sketch

Andrea Alessandretti received the Bachelor’s degree in Electrical and Computer Engineering and the Master’s degree in Informatics and Telecommunication Engineering from the University of Perugia, Italy, in years 2007 and 2010, respectively. During his master studies, he carried out his master thesis at the University of California, Santa Barbara (UCSB). After his MSc education, Andrea was a research fellow for one year at the Institute for Systems and Robotics in Lisbon, Portugal, before starting his doctoral studies within the IST-EPFL Joint Doctoral Initiative, a joint program between the Instituto superior Técnico (IST), in Lisbon, Portugal, and the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. His research interests include nonlinear control systems and model predictive control for tracking and economic optimization, as well as their applications to motion control and coordination of under-actuated vehicles.

Affiliation: Faculty of Engineering, University of Porto (FEUP), Porto, Portugal.

Research interests



Main research goal

Provide theory and tools for the analysis and synthesis of Model Predictive Control (MPC) schemes with closed-loop guarantees.

Tracking MPC, Dissipativity-based Economic MPC, ISS-based Economic MPC

Main application field

Advanced motion control of underactuated vehicles.

Target estimation and tracking via highly observable trajectories, low energy consumption trajectory-tracking, path-following,...



In a classic Tracking-MPC framework, where the main goal is to steer the state of the system to a desired steady-state, the performance index is properly chosen to penalize the distance from the current state to a desired one. In order to capture more complex control objectives, in recent years a growing attention has been dedicated to a new class of controllers that goes under the name of Economic-MPC. Here, the term economic is used to stress the fact that the performance index is a general index of interest that we wish to minimize, e.g., economic, which does not denote the distance to a desired set point. This setting makes full use of the potentialities of optimization-based control strategies. Although, it comes with challenges. In fact, by choosing an arbitrary performance index, it is dicult to predict, and therefore certify, the evolution of the closed-loop system, which could potentially manifest undesirable behaviors.

My research addresses the design of optimization-based control laws with closed-loop guarantees for the case where the objective is the convergence to a desired set-point (Tracking-MPC), the minimization of an arbitrary performance index (Economic-MPC), or a combination of the two (ISS-based Economic MPC).

Selected publications:

A. Alessandretti, A. P. Aguiar, and C. N. Jones On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index Automatica 2016
A. Alessandretti, A. P. Aguiar, and C. N. Jones An Input-to-State-Stability approach to Economic Optimization in Model Predictive Control Trans. on Automatic Control (to appear) 2017
A. Alessandretti, A. P. Aguiar A distributed Model Predictive Control scheme for coordinated output regulation Proc. of the 20th IFAC World World Congress 2017
The ability of combining tracking objectives with economics objectives gives space to a wide range of interesting applications, especially in the field of motion control of underactuated vehicles. The proposed strategies are applied to a range of motion control problems such as trajectory-tracking and path-following distributed formation keeping, energy efficient trajectory-tracking, and target-estimation-and-tracking through highly observable trajectories.

Selected publications:

A. Alessandretti, A. P. Aguiar, and C. N. Jones Trajectory-tracking and Path-following Controllers for Constrained Underactuated Vehicles using Model Predictive Control Proc. of the European Control Conference, Zürich, Switzerland 2013
A. Alessandretti, A. P. Aguiar, and C. N. Jones Optimization based control for target estimation and tracking via highly observable trajectories Proc. of 11th Portuguese Conf. on Automatic Control, Controlo, Porto, Portugal 2014
A. P. Aguiar, A. Rucco, A. Alessandretti A Sampled-Data Model-Predictive Framework for Cooperative Path Following of Multiple Robotic Vehicles Book chapter. To Appear in the Springer ''Lecture Notes in Control and Information Sciences'' 2017

Software

VirtualArena
VirtualArena is an open-source Object-Oriented Matlab IDE for Control Design and System Simulation. For more information about this software, visit the dedicated github page.
A. Alessandretti, A. P. Aguiar, and C. N. Jones VirtualArena : An Object-Oriented MATLAB Toolkit for Control System Design and Simulation Proc. of the 2017 International Conference on Unmanned Aircraft Systems (ICUAS) 2017

For more software, you can check the github page.

Teaching

Control Systems EPFL ME-321 Spring ’12, Fall ’14
Model Predictive Control EPFL ME-425 Spring ’12
Bresciani Mathieu Laurent Motion Control of RC-Cars: theory and experimental validation EPFL Fall ’15
Salazar Villalon Mauro Low-Energy Control EPFL-ETH (Zurich) Fall ’14
Mitjans Marc Collision Avoidance Control Design EPFL-UPC (Barcelona), Zurich Spring ’14
Missiri Salah Eddine Robots Arena: Network Based System for Control of Robotic Vehicles EPFL Fall ’14
Sofia Leo Carmelo Maria Positioning and Visual Locking, Mechanical design EPFL Fall ’14
Konrad Dorian Positioning and Visual Locking, Camera system EPFL Fall ’14
Le Trequesser Benjamin Philippe Positioning and Visual Locking, Modeling and Control EPFL Fall ’14
Leimer Julien Vivian Robotic Monitoring and Surveillance EPFL Fall ’14
Roth Yann Formation Keeping EPFL Spring ’14
Pallaud Marc-Antoine Cooperative Target Tracking EPFL Spring ’14
Asselborn Thibault Optimal control of a hydrofoil boat EPFL Spring ’14
Hansan Xavier Development of Micro-Scale Quadcopter EPFL Fall ’11

Events

Talk On the design of Model Predictive Control schemes for economic optimization and applications to motion control of robotic vehicles. Optimization 2017 6-8 September 2017. Lisbon, Portugal.
Invited session Nonlinear Model Predictive Control for Mechatronic Systems and Motion Control. Organizers: Timm Faulwasser, Juergen Pannek, Andrea Alessandretti. At the IFAC 2017 World Congress 12 July 2017. Toulouse, France.
Invited talk On the design of Model Predictive Control schemes for economic optimization and applications to motion control of robotic vehicles. University of Pennsylvania, UPenn 27 April 2017. Philadelphia, USA.
Workshop Model Predictive Control for Economic Optimization: Theory, design, and applications to motion control of under-actuated vehicles. Marine UAS Workshop. 19-29 June, 2017, Lisbon, Portugal.
Workshop Tools for the design of MPC controllers with economic optimization: application to motion control of robotic vehicles. Marine and Coastal Science (MCS) Workshop. 27 June - 1 July, 2016. Azores, Portugal.
Seminar Continuous-Time Model Predictive Control for Economic Optimization: Theory, Design, and Applications to Motion Control of Underactuated Vehicles Faculty of Engineering, University of Porto (FEUP), April 22nd, 2016. Porto, Portugal.
Workshop Continuous-Time Model Predictive Control for Economic Optimization: Theory, Design, and Applications to Motion Control of Underactuated Vehicles Workshop on Economic and Distributed Model Predictive Control at École Polytechnique Fédérale de Lausanne (EPFL). Organizers: Timm Faulwasser, Colin Jones, Karl Worthmann March 21st-March 22nd, 2016. Lausanne, Switzerland.

Honors

Fellowship

Ph.D. Scholarship Fundação para a Ciência e a Tecnologia (FCT) 2011-2015
Research Scholarship IST-ISR: lnstituto Superior Tecnico (IST), Institute for Systems and Robotics (ISR), Lisbon, Portugal 2010