ph:  ++39.030.3715458, fax: ++39.030.380014

e-mail: marco.campi@unibs.it
wikipage: https://en.wikipedia.org/wiki/Marco_Claudio_Campi

HOT RESEARCH SUBJECTS

• Scenario optimization
• Virtual Reference Feedback Tuning
• Guaranteed regions for identified models (LSCR)
  

New book on the scenario approach:

Bio Sketch

Marco Claudio Campi is Professor of Automatic Control at the University of Brescia, Italy.

In 1988, he received the Doctor degree in electronic engineering from the Politecnico di Milano, Milano, Italy. From 1988 to 1989, he was a Lecturer at the Department of Electrical Engineering of the Politecnico di Milano. From 1989 to 1992, he was a Research Fellow at the Centro di Teoria dei Sistemi of the National Research Council (CNR) in Milano and, in 1992, he joined the University of Brescia, Brescia, Italy. He has held visiting and teaching appointments at the Australian National University, Canberra, Australia; the University of Illinois at Urbana-Champaign, USA;  the Centre for Artificial Intelligence and Robotics, Bangalore, India; the University of Melbourne, Australia; the Kyoto University, Japan; the Texas A&M University, USA; the NASA Langley Research Center, Hampton, Virginia. USA.

Marco Campi is the chair of the Technical Committee IFAC on Modeling, Identification and Signal Processing (MISP), and was the Chair of the Technical Committee IFAC on Stochastic Systems (SS) from 2002 to 2008. He has been in various capacities on the Editorial Board of Automatica, Systems and Control Letters and the European Journal of Control. Marco Campi is a recipient of the "Giorgio Quazza" prize, and, in 2008, he received the IEEE CSS George S. Axelby outstanding paper award for the article The Scenario Approach to Robust Control Design. He has delivered plenary and semi-plenary addresses at major conferences including SYSID, MTNS, and CDC. Currently he is a disinguished lecturer of the Control Systems Society. Marco Campi is a Fellow of IEEE, a Fellow of IFAC, and a member of SIDRA. 

The research interests of Marco Campi include: system identification, stochastic systems, randomized methods, adaptive and data-based control, robust optimization,  and learning theory.

·    research interests
·    projects
·    selected presentations
 
 
 

 
 
 
 
 
 
 
 
 

Research Interests

HOT RESEARCH SUBJECTS:

• Robust convex optimization
• Virtual Reference Feedback Tuning
• Guaranteed regions for identified models (LSCR)
  

·    Air traffic management
See the HYBRIDGE web-page
Collaborators:
Maria Prandini

·    Learning theory
Collaborators:
P.R. Kumar
M.  Vidyasagar
F. Baronio                     

Publication

• Journals
• Book Chapters
• Conferences

Teaching activity

WEB PAGES:
-- Fondamenti di automatica   e   Fondamenti di Automatica A e B

Undergraduate courses:

2010 - System identification and data analysis (University of Brescia)
2002 - 2009 Methodologies and techniques for estimation and system identification (University of Brescia)
1992 -  Fundamentals of systems theory and automatic control (University of Brescia)
1998-2002  Automatic Control (University of Brescia)
1992-1995  System identification (Politecnico di Milano)

Marco Campi has obtained the highest score as an undergraduate instructor in the last academic year.

 
Graduate courses:

January 2020 "From data to decisions: the scenario approach (systems, control, machine learning)"(Indian Institute of Technology, Bombay)
January 2019 "The scenario approach: making decisions in an uncertain world (systems, control, machine learning)" (Yildiz Technical University, Istanbul)
Jenuary 2018   "The scenario approach for systems, control and machine learning" (Supelec, France)
September 2017 "Data-based approaches to uncertain optimization: theory and applications" (Politecnico di Milano)
November 2016 "Scenario Optimization: Heuristics and Certificates in Decision Making" (University of Melbourne)
October 2015 "Introduction to the Scenario Approach" (Texas A&M)
September 2015 "Sample-based approaches to uncertain optimization - theory and applications" (Politecnico di Milano)
February 2015   "The scenario approach for robust control, identification and machine learning" (Supelec, France)
Jenuary 2014   "The scenario approach - Theory and applications" (Supelec, France)
Jenuary 2013   "Uncertain optimization via sample-based approaches" (Supelec, France)
July 2012 "Identification with finitely many data points" (Bertinoro, Italy)
February 2012   "Randomization in systems and control design: the scenario approach" (Supelec, France)
September 2009   "Robust optimization" (Politecnico di Milano)
March 2007   "Learning from data: intrinsic limits and perspectives" (University of Brescia)
Sept. 2006    "System identification and the limits of learning from data" (notes) (Universitat Politecnica de Valencia)
July 2005     Co-instructor at the national graduate school on "Adaptive systems" (Bertinoro, Italy)
Oct. 2002   "What can be learned from data?" (University of Melbourne)
April 2002   "Statistical theory of learning" (Politecnico di Milano)
Gen. 2000   "Data-based design of feedback controllers: direct methods" (University of Melbourne)
July 1999   Co-instructor at the national graduate school on "Statistical methods in identification" (Bertinoro, Italy)
1997-1998   "Frequency domain methods in system identification" (University of Brescia)
1996-1997   "The Kalman filter: theory and applications" (University of Brescia)

Other courses:

September 2016   "Scenario optimization: heuristics and certificate in decision making." (NASA Langley Research Center, Hampton)
October 2015   "Introduction to scenario decision-making." (Texas A&M)
June 2015  "A course on scenario optimization." (NASA Langley Research Center, Hampton)

 
Tutorial courses:

1990-1992 Identification and optimization: tutorial classes (Politecnico di Milano)
1990-1992 Systems theory: tutorial classes (Politecnico di Milano)
1988-1989 Fundamentals of mathematics (Politecnico di Milano)   

PhD students:

Maria Prandini
Thesis title: Adaptive Linear Quadratic Gaussian Control: Optimality Analysis and Robust Controller Design.

Andrea Lecchini
Thesis title: Virtual Reference Iterative Feedback Tuning (VRIFT): a Direct Method for the Iterative Feedback Tuning.

Simone Garatti (co-supervised with Sergio Bittanti)
Thesis title: Assessing the Model Quality in System Identification: the Asymptotic Theory Revisited and Application to Adaptive Control.

Marco Lovera (partial supervision)
Subject: Estimation of process capability indices under non normal distribution assumption.

Matteo Pardo (partial supervision)
Subject: Iterative Methods for Controller Design.

Ivan Serina (partial supervision)
Subject: Nonlinear Function Approximation from Noisy Data.

Andrea Ridolfi (partial supervision)
Subject: Consistency of Bootstrap Estimates of Model Uncertainty in Subspace Identification Methods.

Marco Dalai (partial supervision)
Subject: Guaranteed confidence regions for nonlinear systems through the LSCR (Leave out Sign Dominant Confidence Regions) approach.  

Algo Care'
Thesis title: Data-Based Optimization for Applications to Decision-Making, Identification and Control - A Study of Coverage Properties.
(winner of the 2016 stochastic programming student paper prize)

Martina Favaro

Diego Lorenzi

Graduation committees:

- University of Toulouse, France
- Universitat Politecnica de Valencia
- TU Eindhoven
- University of Twente
- Ecole Polytechnique Federale de Lausanne
- National University of Singapore - NUS

Undergraduate textbooks:

S. Bittanti e M. Campi. Raccolta di problemi di identificazione, filtraggio, controllo adattativo. Pitagora Editrice, Bologna, 1995 (in Italian).
M. Campi. Raccolta di temi d'esame di fondamenti di automatica con soluzione. Casa Editrice Snoopy, Brescia, 1999 (in Italian).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Projects

--  project MURST 40% "System identification, control and signal processing" (1989-1996)
--  special project CNR "Algorithms and architectures for identification and adaptive control" (1991-1992)
--  project MURST 60% "Adaptive and robust control of dynamical systems" (1993-1994)
--  European project Human Capital Mobility "Nonlinear and adaptive control" (1994-1996)
--  European project Human Capital Mobility "System modelling and identification" (1994-1996)
--  project MURST 60% "Adaptive identification, prediction and control" (1995-1997)
--  NATO project Collaborative Research Grant "Adaptive control in an uncertain environment" (1997-1998)
--  co-financed project MURST "New methods for identification and adaptive control of industrial systems" (1997 - 2002)
--  co-financed project MURST "Design criteria for dental implants optimized with respect to bone-implant biomechanical interface stability"
     (1998 - 2000)
--  project MURST 60% "Adaptive and robust control systems" (1998 - 2000)
--  co-financed project MURST "Application of the microwave technology to physico-chemical processing involving solids" (1999 - 2002)
--  European project Research Training Network "Nonlinear and adaptive control" (2000 - )
--  project MURST 60% "System identification techniques based on learning theory" (2001 - 2002)
--  European  IST project "Distributed control and stochastic analysis of hybrid systems supporting safety critical real-time systems design" (HYBRIDGE) (2002 -2005)
--  project MURST 60% "Robust control: design through probabilistic techniques for uncertain convex optimization" (2003)
--  co-financed project MURST "Identification and adaptive control of industrial systems" (2003 - )
--  project MURST 60% "Robust convex optimization: randomized methods and applications to control and system identification" (2004-2005) 
--  project MURST 60% "Identification and contro through robust convex optimization" (2006)   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Plenary and Key-note presentations

Robust convex optimization

--    Slides from the Workshop "CMP'04: Multiple Participant Decision Making", UTIA, Prague, Czech Republic, 12-14 May, 2004.
        Invited plenary lecture: "Decision Making in an Uncertain Environment: the Scenario based Optimization Approach"
 

Papers

G. Calafiore and M.C. Campi.
A learning theory approach to the construction of predictor models.
Discrete and Continuous Dynamical Systems (ISSN 1078-0947), 156:166, supplement volume 2003.

M.C. Campi and G. Calafiore.
Decision Making in an Uncertain Environment: the Scenario based Optimization Approach.
In: Multiple Participant Decision Making (J. Andrysek, M. Karny and J. Kracik eds.). Advanced Knowledge International, pages 99-111, 2004.

G. Calafiore and M.C. Campi.
A Learning Theory Approach to the Construction of Predictor Models.
In: DCDS - Dynamical Systems and Differential Equations, 2003.

G. Calafiore and M.C. Campi.
Interval predictors for unknown dynamical systems: an assessment of reliability.
In Proc. 41st Conf. on Decision and Control, Las Vegas, USA, 2002.

G. Calafiore, M.C. Campi and L. El Ghaui.
Identification of reliable predictor models for unknown systems: a data-consistency aproach based on learning theory.
In Proc. 15th World IFAC Congress, Barcelona, 2002.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Virtual Reference Feedback Tuning
 

Papers

M. C. Campi, A. Lecchini and S.M. Savaresi.
Virtual Reference Feedback Tuning: a Direct Method for the Design of Feedback Controllers.
Automatica, 38:1337-1346, 2002.

M.C. Campi and S.M. Savaresi.
Direct nonlinear control design: the Virtual Reference Feedback Tuning (VRFT) approach.
IEEE Trans. on Automatic Control, AC-51:14-27, 2006.

M.C. Campi, A. Lecchini and S.M. Savaresi.
An application of the virtual reference feedback tuning method to a benchmark problem.
European Journal of Control, Special Issue on  "Design and Optimisation of Restricted Complexity Controllers", 1:66-76, 2003.

A. Lecchini, M.C. Campi and S.M. Savaresi.
Virtual Reference Feedback Tuning for two degree of freedom controllers.
Int. J. Adapt. Control and Signal Process., invited paper for the Special Issue on "New Ideas in Recursive Estimation and stochastic Adaptive Control", 16:355-371, 2002.

M.C. Campi and S. Savaresi.
Virtual reference feedback tuning for nonlinear systems.
In Proc. 44th Conf. on Decision and Control, Seville, Spain, 6608-6613, 2005.

A. Lecchini, M.C. Campi and S.M Savaresi.
Sensitivity shaping via virtual reference feedback tuning.
In Proc. 40th Conf. on Decision and Control, Orlando, pages 750-755, 2001.

A. Lecchini, M.C. Campi and S.M Savaresi.
Virtual reference feedback tuning for two degree of freedom controllers.
European Control Conferece ECC 2001, Porto, 2001.

A. Lecchini, M.C. Campi and S.M Savaresi.
Virtual reference feedback tuning: a new framework for data-based design of PID  and  linear  controllers.
IFAC ALCOSP Workshop, Como, 2001.

M.C. Campi, A. Lecchini and S.M Savaresi.
Virtual reference feedback tuning (VRFT): a new direct approach to the design of feedback controllers.
In Proc. 39th Conf. on Decision and Control, Sydney, pages 623-628, 2000.

M.C. Campi, A. Lecchini, M. Pardo and S. Savaresi.
Iterative feedback tuning: a direct approach.
In Int. Symposium on the Mathematical Theory of Network and Systems, Padova, pages 719-722, 1998.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Guaranteed regions for identified models
 

Papers

M.C. Campi and E. Weyer.
Guaranteed non-asymptotic confidence regions in system identification.
Automatica, 41:1751-1764, 2005.
(the downloadable file is an extended version (with all proofs) of the Automatica paper)

M. Dalai, E. Weyer and M.C. Campi.
Parameter Identification for Nonlinear Systems: Guaranteed Confidence regions through LSCR.
Automatica, in press.

M.C. Campi and E. Weyer.
Identification with finitely many data points: the LSCR approach. 
Semi-plenary presentation. In Proc. Symposium on System Identification, SYSID 2006, New Castle, Australia, 2006.

M.C. Campi, Su Ki Ooi and E. Weyer.
Non-asymptotic quality assessment of generalised FIR models with periodic inputs.
Automatica, 40:2029-2041, 2004. 

M.C. Campi and E. Weyer.
Finite sample properties of system identification methods.
IEEE Trans. on Automatic Control, AC-47:1329-1334, 2002.

E. Weyer and M.C. Campi.
Non-asymptotic confidence ellipsoids for the least squares estimate.
Automatica, 38:1529-1547, 2002.

M.C. Campi and E. Weyer.
Non-asymptotic confidence sets for input-output transfer functions.
In Proc. 45th Conf. on Decision and Control, San Diego, CA, USA, 157-162. 2006.

M. Dalai, E. Weyer and M.C. Campi.
Parametric identification of nonlinear systems: Guaranteed confidence regions.
In Proc. 44th Conf. on Decision and Control, Seville, Spain, 6418-6423, 2005.

E. Weyer and M.C. Campi.
Global non-asymptotic confidence sets for general linear models.
In Proc. 16th World IFAC Congress, Prague, 2005.

M.C. Campi and E. Weyer.
Non-asymptotic confidence sets for the parameters of ARMAX models.
In Proc. IFAC Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP 2004), Yokohama, Japan, 2004.

M.C. Campi, E. Weyer
Estimation of confidence regions for the parameters of ARMA models - guaranted non-asymptotic results.
In Proc. 42st Conf. on Decision and Control, Maui, Hawaii, USA , 2003.

Su Ki Ooi, E. Weyer and M.C. Campi.
Finite sample quality assessment of system identification models of irrigation channels.
2003 IEEE Conference on Control Applications, Istanbul, 2003.

M.C. Campi, Su Ki Ooi and E. Weyer.
Non-asymptotic quality assessment of generalised FIR models.
In Proc. 41st Conf. on Decision and Control, Las Vegas, USA, 2002.

M.C. Campi, E. Weyer and Su Ki Ooi.
Nonasymptotic quality assessment of identified models.
In Proc. 15th World IFAC Congress, Barcelona, 2002.

E. Weyer and M.C. Campi.
Non-asymptotic confidence ellipsoids for the least squares estimate.
In Proc. 39th Conf. on Decision and Control, Sydney, pages 2688-2693, 2000.

E. Weyer and M.C. Campi.
Finite sample properties in system identification methods.
In Proc. 38th Conf. on Decision and Control, Phoenix, 1999.