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| ADAPTATION AND LEARNING IN CONTROL AND SIGNAL PROCESSING 2001
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A Proceedings volume from the IFAC Workshop, Cernobbio-Como, Italy, 29-31 August 2001
By
S. Bittanti, Dipartimento di Electtronica e Informazione, Politecnico di Milano, Italy
Included in series
IFAC Proceedings Volumes,
Description
In control and signal processing, adaptation is a natural tool to cope with real-time changes in the dynamical behaviour of signals and
systems. In this area, strongly connected with prediction and identification, there has been an increasing interest in switching and
supervising methods. Moreover in recent years, special attention has been paid to the ideas evolving round the theory of statistical
learning as a potential tool of improved adaptation.
The IFAC workshop on Adaptation and Learning in Control and Signal Processing
in 2001 gathered together experts in the field and interested researchers from universities and industry to present a full picture of
the area. This proceedings volume presents papers covering the following subjects: Model reference and predictive control; Multiple
model control; Adaptive control I/II; Adaptive control and learning; Learning; Adaptive control of nonlinear systems I/II; Supervisory
control; Neural networks for control; PID design methods; Sliding mode; Adaptive filtering and estimation; Identification methods I/II.
Audience
For experts and researchers in the field of signal processing.
Contents
Selected Papers
.
Plenary Paper
.
Nonlinear identification and adaptive control of combustion engines
(R. Isermann, N. Müller)
Model Reference and Predictive Control
.
Identification-oriented predictive control
(L.C. Kammer, G.A. Dumont).
An alternate new gap metric for robustness measure (L. Keviczky, Cs. Bányász).
Model reference
adaptive control of non-linear multivariable systems using an interactor structure estimation (Y. Mutoh).
Robust MRAC of a linear time-varying
parabolic system with bounded disturbance (K-J. Yang et al.).
Applications to Mechanical and Bio-Mechanical Systems
.
Identification for the moving objects by using the observed image data (X. Chen, G. Zhai)
Identification of a biomechanical system using
neural networks (T. Schauer et al.).
Decentralized adaptive continuous-time control of coupled drives apparatus (V. Bobál et al.).
A simplified model for head-neck segment fast movements in the frontal plane (A. Pedrocchi et al.).
Adaptive Control and Learning
.
A Comparison of optimal iterative learning control schemes (M. Rzewuski et al.).
Virtual reference feedback tuning: a new framework for data-based design of PID and linear controllers (A. Lecchini et al.).
Efficient linear MIMO adaptive inverse control (G.L. Plett).
Norm optimal iterative learning control applied to chain conveyor systems
(T. Al-Towaim et al.).
Neural Networks for Control
.
RBFN model adaptation based on orthogonal decomposition
(D.L. Yu, J.B. Gomm).
Approximating networks for the solution of T-stage stochastic optimal control problems (M. Baglietto et al.).
Neural network based min-max predictive control. Application to a heat exchanger (D.R. Ramírez et al.).
A design of
neural-net based generalized minimum variance controller (Y. Ohnishi et al.).
Multiple Model Control
.
Safe switching in multi-controller implementation (B.D.O. Anderson et al.).
Multiple model adaptive estimation for multiuser
detection on CDMA communication (M.H. Jaward et al.).
Guaranteed closed loop precision in multiple model based control (J.
Diez, F. Previdi).
Local linear modeling for control of batch processes (D. Bonné, S.B. Jørgensen).
Adaptive
Control I
.
An extension of self-tuning GMVC based on state-space approach (A. Yanou et al.).
Overparametrization
in predictive adaptive control: experimental results and an entropy interpretation (J.M. Lemos).
Adaptive control of a two input -
two output system (M. Kubalcík, V. Bobál).
Adaptive control using controllers of restricted structure (M.J. Grimble,
P. Martin).
Learning
.
Applications of statistical-learning methods in systems and control (M. Ariola et
al.).
A new system identification method based on support vector machines (S. Adachi, T. Ogawa).
Non-parametric heavy-tailed
density estimation and classification problem (N.M. Markovitch, U.R. Krieger).
Torques generation for driving an insect-like robot
by evolutionary learning approach (A. Pedrocchi et al.).
Adaptation and learning in neural networks multiple models based control
of mobile robots (A. D'Amico et al.).
PID Design Methods
.
Self-Tuning two-degree-of-freedom pid
compensator based on two-degree-of-freedom generalized minimum
variance control (T. Sato et al.).
Relay based gain and phase
margins iterative PID controller design (G.H.M. de Arruda, P.R. Barros).
A design of evolutionary tuning PID controllers (T. Yamamoto et al.).
A design of multiloop predictive self-tuning PID controllers (M. Katayama et al.).
Adaptive
Control of Nonlinear Systems I
.
Adaptive control of the power factor precompensator: a comparative study (G. Kaliora, A.
Astolfi).
Adaptive compensation of nonlinearity in high power amplifier by support vector machine (T. Eda et al.).
An heuristic
learning modelling strategy for nonlinear systems
(G.L. Santosuosso).
Adaptive predictive fault tolerant control of super-heated steam
temperature in an industrial boiler (R.V. Dionísio et al.).
Applications To Power Plants and Software Tools
.
Realization in MATLAB-SIGLAB environment of a real time estimator of the damping of the electromechanical
mode of the alternator-network
system(C.L. Brasca, A. Danelli).
Adaptive tracking control of nonlinear power converters (E.F. Colet, A.S.I. Zinober).
TIDEA: A control
system fine tuning software tool applied to a large power station (F. Pretolani et al.).
MATLAB-toolbox for CAD of simple self-tuning
controllers (V. Bobál et al.).
Supervisory Control
.
Feedback-loop monitoring for controller
falsification (T. Agnoloni et al.).
Design method for robust supervisor controller (T. Nakajima et al.).
Fault
detection and isolation applied to the supervision of adaptive control systems: a neural network
based scheme (F.V. Barajas, R.A. Ramírez
Mendoza)
Sliding mode
.
Sliding mode control with adaptive decrease of chattering (R. Gessing).
Sliding mode
control for systems with unknown control direction
(G. Bartolini et al.).
Plenary Paper II
.
Turbo-learning:
A novel application to MIMO wireless communications (S. Haykin, M. Sellathurai).
Adaptive Filtering and Estimation
.
New
time-varying LMS and RLS algorithms with application to direction-of-arrival tracking (K. Yanagihara et al.).
The accelerating
adaptive filtering algorithm (P.E. Jojoa et al.).
Adaptive notch filter with global stability (T. Suzuki, K. Hamada).
Robust
wiener design of adaptation laws with constant gains
(M. Sternad et al.).
Application to Mechanical Systems
.
Longitudinal
Attitude control of a small aircraft using cascade LCN's (T. Caetano et al.).
On-line tuning of one-mass motor drive system
by simple adaptive control (T. Sekiai et al.).
Direct adaptive predictive control of an automatic gear box (G. Ramond et
al.).
A road-adaptive LQG control for semi-active suspension systems (H-C. Sohn et al.).
Identification
Methods I
.
Parameter identification for a scalar linear system with fractional brownian motion (T.E. Duncan, B. Pasik-Duncan).
An iterative subspace identification with observation outliers based on weighted orthogonal decomposition (H. Tanaka, T. Katayama).
Identification of linear parameter varying models using kalman filtering (M. Lovera, F. Previdi).
A new adaptive identification method
of critical point using frequency estimator (M. Saeki, H. Takeuchi).
Adaptive Control of Nonlinear Systems II
.
One approach to adaptive control of nonlinear processes (P. Dostál et al.).
Design of controller for nonlinear systems
by the gain scheduling technique (P. Dobra).
Adaptive nonlinear H∞ control for processes with bounded variations of parameters
- general forms and general
relative degree case (Y. Miyasato).
Adaptive iterative refinement of an optimal 2DF nonlinear controller
(L. Keviczky, Cs. Bányász)
Identification Methods II
.
Remarks on the sample complexity for linear
control systems identification (P. Kuusela et al.).
The EM algorithm for multivariable dynamic system estimation
(B. Ninness,
S. Gibson).
Neurofuzzy state space modelling and control using kalman filtering state feedback with coloured noise (C.J. Harris, X.
Hong).
Penalized identification for self-tuning control: an overview
(S. Bittanti et al.).
Adaptive Control
II
On the design of direct adaptive controllers (F.M. Pait).
Adaptive control of technological processes based on dual
youla-kucera parametrization (F. Gazdoş, P. Dostál).
Transient performance improvement in discrete-time model reference
adaptive controllers by filtering
estimated parameters (N. Mizuno, Y. Fukui).
Adaptive pole assignment control under constraints (A.
Królikowski, R. Stawski).
| Bibliographic details |
Paperback, 502 pages, publication date: SEP-2002
ISBN-13: 978-0-08-043683-8
ISBN-10: 0-08-043683-8
Imprint: PERGAMON
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