Series Editor
Bernard Dubuisson
First published 2017 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd
27-37 St George’s Road
London SW19 4EU
UK
www.iste.co.uk
John Wiley & Sons, Inc.
111 River Street
Hoboken, NJ 07030
USA
www.wiley.com
© ISTE Ltd 2017
The rights of Dumitru Popescu, Amira Gharbi, Dan Stefanoiu and Pierre Borne to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Library of Congress Control Number: 2017930552
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78630-014-0
The purpose of this book is to present the various aspects and the different approaches most commonly employed in the control of industrial processes.
Considering that process control design is carried out using a model based approach, the modeling and identification of the systems are presented with the main objective of producing dynamic control models.
Using the chosen model, the control system is determined so as to ensure that the process satisfies the required level of performance. In the case of linear models, the main methods used in control design are based on the notion of pole placement.
In order to account for the fact that the chosen model is only a simplified and often imperfect description of the process’ behavior, more elaborate controls can be suggested: adaptive control, predictive control, internal model control, etc.
When the behavior of the process is strongly nonlinear, the use of a multimodel control can become necessary. The determination, choice and consideration of the various models that can describe the evolution of the process at various operating points depend on the validity of each of these models at the chosen operating points.
We propose a method for estimating the error induced by the models’ own estimation difficulties, and by the presence of uncertainties, noise and bounded perturbations.
After presenting the physical laws that govern the evolution of continuous variation processes, we go on to to explore in detail several real optimized control solutions, carried out in an industrial setting, providing the reader with a better understanding of the approaches developed.
Dumitru POPESCU, Amira GHARBI,
Dan STEFANOIU and Pierre BORNE
February 2017
Dynamic control model | |
Dynamic tracking model | |
AF-CLOE | Adaptively Filtered Closed Loop Output Error (identification method) |
A,B,C,D | State-space representation of the continuous MIMO system |
Ad,Bd,Cd,Dd | State-space representation of the discrete MIMO system |
A,b,c,d | State-space representation of the continuous SISO system |
Ad,bd,cd,dd | State-space representation of the discrete SISO system |
ARMAX | Model or class of identification models expressed by 3 terms: autoregressive (AR), moving average (MA) and exogenous control (X) |
ARX | Identification model of autoregressive type (AR), with exogenous control (X) |
(C,M) | Closed loop nominal system |
(C,P) | Closed loop real system |
DPRC | Differential Pressure Control System |
FRC | Flow Control System |
LRC | Level Control System |
LS | Least Squares identification technique |
RLS | Recursive Least Squares identification technique |
PID | Proportional-integral-derivative algorithm |
PRC | Pressure Control System |
SM | State Model |
TRC | Temperature Control System |
BJ | Identification model of Box-Jenkins type |
CL | Closed Loop (system, identification method etc.) |
CLOE | Closed Loop Output Error (idenfication methods) |
CLSI | Closed Loop System Identification |
dB | decibel(s) – measuring unit for the signals/systems spectra |
E-LSM | Extended Least Squares Method |
F-CLOE | Filtered Closed Loop Output Error (identification method) |
FIR | Finite Impulse Response (filter, system) |
FT | Fourier Transform |
G-CLOE | Generalized Closed Loop Output Error (identification method that replaces ARX model by BJ model) |
G-LS | Generalized Least Squares (PEMM for the BJ model) |
G(s) | Continuous system transfer function |
G(z) | Discrete system transfer function |
GR(z-1), GS(z-1) | Pre-specified polynomials for robust control |
I-CLOE | Integral Closed Loop Output Error (identification method)I/O Input-Output (type of identification model, transformation, operator, etc.) |
IIR | Infinite Impulse Response (filter, system) |
I=f(V) | Photovoltaic Current-Voltage characteristic |
L | Estimator matrix |
LSM | Least Squares Method |
M | Sylvester matrix |
MIMO | Multi-Input Multi-Output (type of fully multi-variable model or system or process) |
MISO | Multi-Input Single-Output (type of multi-variable model or system or process with several inputs and on single output) |
MV-LSM | Multi-Variable Least Squares Method |
OL | Open Loop (system, identification etc.) |
OLOE | Open Loop Output Error (identification method) |
OLSI | Open Loop System Identification |
PEMM | Prediction Error Minimization Method (identification method) |
P(z-1) | Characteristic polynomial of the system |
P=f(I,V) | Photovoltaic Power-Current, Voltage characterstic |
PRS | Pseudo-Random signal |
PV | Photovoltaic pannel |
Q | Observability matrix |
R | Controlability matrix |
R-ELS | Recursive Extended Least Squares (identification method) |
RST | Automatic regulator with 3 polynomials: R (regulation), S (sensitivity) and T (tracking) |
RST-YK | RST regulator expressed in Youla-Kucera parametric form |
SI | System identification |
SISO | Single-Input Single-Output (type of model or system or process with one input and one output) |
SNR | Signal-to-Noise Ratio |
Svy(jω) | Disturbance-output sensitivity function |
W-CLOE | Weighted Closed Loop Output Error (identification method) |
X-CLOE | Extended Closed Loop Output Error (identification method that replaces ARX model with ARMAX model) |
X-OLOE | Extended Open Loop Output Error (identification method employed in case of ARMAX model instead of ARX model) |
YK | Youla-Kucera (parametric expressions of a regulator) |
|∆M (jω)| | Modulus margin of the system robustness |