Table Of ContentAdvances in Industrial Control
Springer-Verlag London Ltd.
Other titles published in this Series:
System Identification and Robust Control
Steen Toffner-Clausen
Genetic Algorithms for Control and Signal Processing
K.F. Man, K.S. Tang, S. Kwong and W.A. Halan g
Advanced Control of Solar Plants
E.F. Camacho, M. Berenguel and F.R. Rubio
Control of Modern Integrated Power Systems
E. Mariani and S.S. Murthy
Advanced Load Dispatch for Power Systems: Principles, Practices and Economies
E. Mariani and S.S. Murthy
Supervision and Control for Industrial Processes
Björn Sohlberg
Modelling and Simulation of Human Behaviour in System Control
Pietro Carlo Cacciabue
Modelling and Identification in Robotics
Krzysztof Kozlowski
Spacecraft Navigation and Guidance
Maxwell Noton
Robust Estimation and Failure Detection
Rami Mangoubi
Adaptive Internal Model Control
Aniruddha Datta
Price-Based Commitment Decisions in the Electricity Market
Eric Allen and Marij a Ilic
Compressor Surge and Rotating Stall
Jan Tommy Gravdahl and Olav Egeland
Radiotherapy Treatment Planning
Oliver Haas
Feedback Control Theory For Dynamic Traffic Assignment
Pushkin Kachroo and Kaan Özbay
Control Instrumentation for Wastewater Treatment Plants
Reza Katebi, Michael A. Johnson an d Jacqueline Wilkie
AutotuningofPID Controllers
Cheng-Ching Yu
Robust Aeroservoelastic Stability Analysis
Rick Lind and Marty Brenner
Biao Huang and Sirish L. Shah
Performance Assessment
of Control Loops
Theory and Applications
With 102 Figures
Springer
Biao Huang, PhD
Sirish L. Shah, PhD
Department of Chemical and Materials Engineering, University of Alberta,
Edmonton, Alberta, Canada, T6G 2G6
ISBN 978-1-4471-1135-1
British Library Cataloguing in Publication Data
Huang, Biao, 1962-
Performance assessment of control loops : theory and
Applications. - (Advances in industrial control)
1. Automatic control
I. Title II. Shah, S. L. (Sirish L.), 1949-
629.8
ISBN 978-1-4471-1135-1
Library of Congress Cataloging-in-Publication Data
Huang, Biao
Performance assessment of control loops : theory and applications
Biao Huang and Sirish L. Shah,
p. cm.
Includes biblipgraphical references.
ISBN 978-1-4471-1135-1 ISBN 978-1-4471-0415-5 (eBook)
DOI 10.1007/978-1-4471-0415-5
1. Automatic control. 2. Control theory. 3. Algorithms.
I. Shah. S. L. (Sirish L.), 1949- . I.I Title.
TJ213.H83 1999 99-31704
629.8—dc21 CIP
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, mis 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 of licences issued
by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be
sent to the publishers.
© Springer-Verlag London 1999
Originally published by Springer-Verlag London Limited in 1999
Softcover reprint of the hardcover 1st edition 1999
M ATI AB® and SIMULINK® are the registered trademarks of The MathWorks, Inc., http://www.mathworks.com
A significant portion of the material in this book has been reprinted from various journals and appears
with permission from Elsevier Science and the Canadian Journal of Chemical Engineering. For the full
citations of the papers involved please refer to page 7.
The use of registered names, trademarks, etc. in this publication does not imply, even in teh absence of a
specific statement, that such names are exempt from the relevant laws adn regulations and therefore free
for general use.
The publisher makes no representation, express or implied, with regard to the accurayc of the
information contained in this book and cannot accept any legal responsibility or liability for any errors
or omissions that may be made.
Typesetting: Camera ready by authors
69/3830-543210 Printed on acid-free paper SPIN 10728715
Advancesin Industrial Control
SeriesEditors
ProfessorMichaelJ.Grimble,ProfessorofIndustrialSystemsandDirector
ProfessorMichaelA.Johnson,ProfessorofControlSystemsandDeputyDirector
IndustrialControlCentre
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SERIESEDITORS' FOREWORD
The series Advances in Industrial Control aims to report and encourage
technology transfer in control engineering. The rapid development of control
technologyhas an impactonall areasofthe control discipline. New theory, new
controllers,actuators, sensors, newindustrialprocesses, computermethods, new
applications, new philosophies..., new challenges. Much of this development
work resides in industrial reports, feasibility study papers and the reports of
advanced collaborative projects. The series offers an opportunityfor researchers
to present an extended exposition ofsuch new work in all aspects ofindustrial
controlforwiderandrapiddissemination.
Benchmarkingisatechniquefirst appliedbyRankXeroxin the late 1970sfor
business processes. As a subject in the commercial arena, benchmarking thrives
with, for example, a European Benchmarking Forum. It has taken rather longer
forbenchmarkingtomake thetransfertothetechnicaldomainandevennowthe
subjectismakingaslowheadway. Akeyresearch stepinthisdirectionwas taken
by Harris (1989) who used minimum variance control as a benchmark for
controller loop assessment. This contribution opened up the area and a
significant specialist literature has now developed. Significant support for the
methodologywasgivenbyHoneywellwhohavecontrollerassessmentroutines in
their process control applications software; therefore, it is timely to welcome a
(first) monograph on controller performance assessment by Biao Huang and
Sirish Shah to the Advances in Industrial Control series. Industrial engineers,
process controlengineers and the academic control communityshould find this
structuredpresentationofthis newclass ofoperationaltechniques invaluable for
self-studyorassupplementarytaughtcoursematerial.
M.J. GrimbleandM.A. Johnson
IndustrialControlCentre
Glasgow,Scotland,U.K.
June, 1999
PREFACE
The design of advanced control algorithms has largely preoccupied the con
trol practitioner's efforts. The rationale has been that systems which are
difficult to control need advanced optimal, non-linear, adaptive or like con
trol algorithms for better regulation. Although there is a variety of control
design techniques, such as L1, H2, Hoo, etc., few techniques exist for ob
jective measures ofcontrol loop performance or, conversely, measures of the
level ofdifficulty in controlling a process variable from routine operating in
dustrial process data. The control literature is relatively sparse on studies
concerned with such proper or formal measures ofcontrol loop performance.
The purpose of this monograph is to expose the reader to the most recent
techniques for controller performance assessment. Specifically, this text pon
ders questions such as the following: Is your controller healthy? Is it doing
its job well? How can one obtain a non-invasive or a model-free assessment
ofcontroller performance?
PerformanceAssessmentof
SISOIMIMOcontrollers
enablesonetoasksimplistically:
Howhealthyisyourcontroller?
Isitdoingitsjobwell?
v
y
Fig. 0.1. A simplistic depiction of the performance assessment problem.
xii Preface
One of the motivating factors as to why the industrial practitioner and
the academic researcher may want to investigate this area is the explosive
growth in the amount ofprocess data that is available for analysis. In almost
all process environments, ranging from petroleum refining to pulp and paper
processing, easy data access through Distributed Control Systems (DCS)
is now a rule rather than an exception. In fact, in most process industries
data is collected and simply archived. Estimates indicate that most chemical
plants require over 100 gigabytes of storage space to archive a year's worth
ofdata. The data-warehousing problem is a manifestation ofthe exponential
increasein information flow as a result ofthe recent advances in networksand
computers. In summary, we live in an information age in which the process
industry world is awash with data. Properly archived, screened and sorted
data can be a tremendous source of information. The question is how to
extract useful information from this data and then put it to good use? The
main objective of this research monograph is to suggest how routine closed
loop data can be used to obtain non-invasive measures of the performance
of the control loops in the plant. The theoretical results are supported by
simulation plus experimental (in laboratory) and industrial evaluations.
An equally important motivation for the recent interest in this area is
an economic one. A typical industrial process includes thousands of con
trol loops. Instrumentation technicians generally maintain and service these
loops, but rather infrequently. Routine maintenance ofsuch loops at optimal
settings can save a typical chemical complex hundreds ofthousands ofdollars
a year. The development ofquality measures of performance for such control
loops in industrial settings is therefore an important area ofindustrial inter
est. Controller monitoring falls in the realm ofenterprise asset management.
The thinking is that controllers, whether basic (i.e., PID type) or advanced,
should be treated like other capital assets and they should therefore be mon
itored on a routine basis.
Thefollowing synopsisoutlines the major ingredientsofthis book. Perfor
mance assessmentofunivariatecontrol loops is first carriedout by comparing
the actual output variance with the minimum variance. The latter term is es
timated by simple time series analysis of routine closed-loop operating data.
The only prerequisite information required is knowledge ofthe process delay.
When the process has a unit delay, then a whiteness test can be applied to
the output as is typically done via the Shewhart chart. The analysis of the
same problem in thefrequency domain has not received much attention in the
literature. Preliminary results in this areaare presented here as they comple
ment the time-domain analysis very well and provide an added perspective
on the controller performance assessment problem.
The univariate performance assessment concepts are then extended to the
multivariate case. Akey to performance assessmentofmultivariate processes,
using minimum variance control as a benchmark, is to estimate the bench
mark performance from routine operating data with a priori knowledge of
