Welcome to the homepage of
M.C. Campi (Marco Campi)
ph: ++39.030.3715458, fax: ++39.030.380014
e-mail: campi@ing.unibs.it
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 Research Assistant at the Department of Electrical Engineering of the Politecnico di Milano. From 1989 to 1992, he worked as a Researcher 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 positions at many universities and institutions including 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.
Prof. Campi is an Associate Editor of Systems
and Control Letters, and a past Associate Editor of Automatica
and
the
European
Journal of Control. From 2002 to 2008, he served as Chair of
the Technical
Committee IFAC on Stochastic Systems (SS) and he is
currently vice-chair for the Technical
Committee IFAC on Modeling, Identification and Signal Processing (MISP).
Moreover, he is a distinguished lecturer of the Control Systems
Society. Marco Campi's doctoral thesis was awarded the
"Giorgio
Quazza" prize as the best original thesis for year 1988. In 2008, he
received the IEEE CSS George S. Axelby outstanding paper award
for the article The Scenario Approach to Robust
Control
Design, co-authored
with G. Calafiore.
The research interests of Marco Campi include: system
identification, stochastic systems, adaptive and
data-based
control, robust convex
optimization,
robust
control and estimation, and learning theory.
· research interests
· projects
· selected
presentations
HOT RESEARCH SUBJECTS:
· Robust control
Collaborators: Giuseppe
Calafiore
· Air traffic management.
See the HYBRIDGE
web-page
Collaborators: John
Lygeros
Maria
Prandini
· Learning Theory
Collaborators: P.R.
Kumar
M.
Vidyasagar
· Iterative schemes for controller design
Collaborators: Sergio
Bittanti
Simone
Garatti
· Nonlinear regression
Collaborators: P.R.
Kumar
Maria
Prandini
Ivan
Serina
WEB PAGES:
-- Fondamenti di Automatica A e B
Undergraduate courses:
2002 - 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:
March 2997 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:
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:
1. Maria Prandini
Thesis title: Adaptive Linear Quadratic Gaussian Control:
Optimality
Analysis and Robust Controller Design.
2. Andrea Lecchini
Thesis title: Virtual Reference Iterative Feedback Tuning (VRIFT):
a Direct Method for the Iterative Feedback Tuning.
3. 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.
4. Marco Lovera
(partial supervision)
Subject: Estimation of process capability indices under non normal
distribution assumption.
5. Matteo Pardo
(partial supervision)
Subject: Iterative Methods for Controller Design.
6. Ivan Serina
(partial supervision)
Subject: Nonlinear Function Approximation from Noisy Data.
7. Andrea Ridolfi
(partial supervision)
Subject: Consistency of Bootstrap Estimates of Model Uncertainty
in Subspace Identification Methods.
8. Marco Dalai
(partial supervision)
Subject: Guaranteed confidence regions for nonlinear systems
through the LSCR (Leave out Sign Dominant Confidence Regions) approach.
Graduation committees:
- Universitat Politecnica de Valencia
- TU Eindhoven
- University of Twente
- Ecole Polytechnique Federale de Lausanne
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)
Selected
presentations and invited courses
-- 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.