Welcome to the homepage of
M.C. Campi (Marco Campi)
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:
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 member 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
HOT RESEARCH SUBJECTS:
· Air
traffic management
See the HYBRIDGE
web-page
Collaborators:
Maria
Prandini
· Learning
theory
Collaborators:
P.R.
Kumar
M.
Vidyasagar
F. Baronio
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).
-- 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
-- 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.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.