Frontiers in adaptive control

344 Pages·36.22 MB·English

by  edited by Shuang Cong.

Frontiers in Adaptive Control

Frontiers in Adaptive Control

Edited by
Shuang Cong

In-Tech
intechweb.org
Published by In-Tech

In-Tech
Kirchengasse 43/3, A-1070 Vienna, Austria
Hosti 80b, 51000 Rijeka, Croatia

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© 2009 In-tech
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First published January 2009
Printed in Croatia

Frontiers in Adaptive Control, Edited by Shuang Cong
p. cm.
ISBN 978-953-7619-43-5
1. Adaptive Control I. Shuang Cong
V

Preface

Starting in the early 1950s, the design of autopilots for high performance aircraft moti-
vated an intense research activity in adaptive control. Today, adaptive control theory has
grown to be a rigorous and mature discipline. Because it is good at dealing with uncertain
quantities in dynamic systems in which exist unknown parameters and disturbances, adap-
tive control has become more popular in many fields of engineering and science in terms of
algorithms, design techniques, analytical tools, and modifications. Nowadays, the presence
of robotics in human-oriented applications demands control paradigms to face partly
known, unstructured, and time-varying environments. Variety disturbances including ap-
plied external forces, higher order dynamics, nonlinearities and noise are always present in
complex control systems such as robot manipulators and the human-machine ensemble.
Adaptive control is required to be applied into new fields and more complex situations.

The objective of this book is to provide an up-to-date and state-of-the-art coverage of di-
verse aspects related to adaptive control theory, methodologies and applications. These in-
clude various robust techniques, performance enhancement techniques, techniques with less
a-priori knowledge, nonlinear adaptive control techniques and intelligent adaptive tech-
niques. There are several themes in this book which instance both the maturity and the
novelty of the general adaptive control. The book consists of 17 Chapters. Each chapter is
introduced by a brief preamble providing the background and objectives of subject matter.
The experiment results are presented in considerable detail in order to facilitate the compre-
hension of the theoretical development, as well as to increase sensitivity of applications in
practical problems. The outline of each chapter is as follows:

In Chapter 1, an adaptive control for a free-floating space robot is proposed by using the
inverted chain approach, which is a unique formulation for a space robot compared with
that for a ground-based manipulator system. Chapter 2 deals with introducing how to ob-
tain models linear in parameters for real systems and then using observations from the sys-
tem to estimate the parameters or to fit the models to the systems with a practical view. A
new procedure for model validation in the frequency domain is presented in Chapter 3. This
procedure permits to validate or invalidate models over certain frequency ranges. The pro-
cedure is the translation of a time domain residual whiteness test to a frequency dependent
residual whiteness test. The counterpart on the frequency domain of a time domain white-
ness test is established.
In the methodologies, substantial progress of the Kalman filtering design for nonlinear
stochastic systems made in the past decade offers promise for solving some long-standing
control problems, which is considered in Chapter 4. In Chapter 5, a backstepping-like pro-
cedure incorporating the model reference adaptive control (MRAC) is employed to circum-
vent the difficulty introduced by its cascade structure and various uncertainties. A
Lyapunov-like analysis is used to justify the closed-loop stability and boundedness of inter-
nal signals. In Chapter 6, a novel Takagi-Sugeno(TS) Feedforward fuzzy approxima-
tor(FFA)-based adaptive control scheme is proposed and applied to motion/force tracking
VI
control of holonomic systems. By integrating the feed-forward fuzzy compensation and er-
ror-feedback concepts, the proposed FFA-based control concept avoids heavy computation
load and achieves global control results. In Chapter 7, two sliding mode adaptive control
strategies have been proposed for single-input single-output(SISO) and single-input multi-
ple-output(SIMO) systems with unknown bound time-varying uncertainty respectively.
Chapter 8 introduces the Active Observer (AOB) algorithm for robotic manipulation. The
AOB reformulates the classical Kalman filter (CKF) to accomplish MRAC. The AOB pro-
vides a methodology to achieve model-reference adaptive control through extra states and
stochastic design in the framework of Kalman filters. In Chapter 9, the human-machine en-
semble is regarded as an adaptive controller where both the environment and human cogni-
tion vary, the latter due to environmental and situational demands. Chapter 10 presents a
parameter estimation routine that allows exact reconstruction of the unknown parameters in
finite-time provided a given excitation condition is satisfied. The robustness of the routine to
an unknown bounded disturbance or modeling error is also shown. In Chapter 11, a general
scheme to construct adaptive policies in control models is to combine statistical estimation
methods of the unknown distribution with control procedures. Such policies have opti-
mality properties provided that the estimators are consistent in an appropriate sense. Chap-
ter 12 develops a new adaptive control framework which applies to any nonlinearly param-
eterized system satisfying a general Lipschitzian property. This allows one to extend the
scope of adaptive control to handle very general control problems of nonlinear parameteri-
zation since Lipschitzian parameterizations include as special cases convex/concave and
smooth parameterizations. Chapter 13 presents a simple and straightforward adaptive con-
troller strategy from the class of direct methods, based on reference models. The algorithm
offers an alternative solution to the burden of process identification, and will present possi-
bilities to tune both integer-and fractional-order controllers.
In the applications, Chapter 14 considers yaw dynamics of a vehicle operating under un-
certain road conditions with unknown velocity and mass. Authors develop an adaptive con-
trol design technique motivated by the demand for a system capable of adjusting to devi-
ations in vehicle parameters with almost negligible performance compromises. Chapter 15
proposes an indirect multiple -input multiple-output (MIMO) MRACS with structural esti-
mation of the interactor. By using indirect method, unreasonable assumptions such as as-
suming the diagonal degrees of interactor can be avoided. Since the controller parameters
are calculated based on the observability canonical realization of the estimated values, the
proposed method is suitable for on-line calculations. Chapter 16 discourses on adaptive con-
trol for wireless local area networks introducing the Priority Oriented Adaptive Control
with QoS Guarantee (POAC-QG) protocol for WLANs. It can be adapted into the Hybrid
Control Function (HCF) protocol of the IEEE 802.11e standard in place of Hybrid Control
Channel Access (HCCA). A Time Division Multiple Access (TDMA) scheme is adopted for
the access mechanism. POAC-QG is designed to efficiently support all types of real-time
traffic. Chapter 17 surveyed various topics in Very Large Scale Integrated (VLSI) technology
in adaptive control perspective: The design margins in process and circuit level are con-
sidered to be headroom for power savings, and adaptive control schemes are used to figure
out the margins automatically and to make adjustment without harming the system oper-
ation. An adaptive control is also used to optimize the circuit operation for time-varying cir-
cumstances. This type of scheme enables the chip to operate always in optimal condition for
wide range of operation conditions.
I believe the new algorithms and adaptive control strategies presented in this book are
very effective approaches to solve the problems in unknown parameter estimation, model-
VII
ing, analysis, adaptive controller design and some important research challenge. The book is
also intended to be served as a reference for the researcher as well as the practitioner who
wants to solve the problems caused by the uncertainty in the controlled systems. I hope that
the reader will share my excitement to present this book on frontiers in adaptive control and
will find it useful.
Finally, I would like to thanks all the authors of each Chapter for their contribution to
make this book possible. My special thanks go to the publisher, In-Tech, for publishing this
book.

Shuang Cong
University of Science and Technology of China
P. R. China
[email protected]

IX

Contents

Preface V

1. An Adaptive Control for a Free-Floating Space Robot by Using Inverted 001
Chain Approach
Satoko Abiko and Gerd Hirzinger

2. On-line Parameters Estimation with Application to Electrical Drives 017
Navid R. Abjadi, Javad Askari, Marzieh Kamali and Jafar Soltani

3. A New Frequency Dependent Approach to Model Validation 031
Pedro Balaguer and Ramon Vilanova

4. Fast Particle Filters and Their Applications to Adaptive Control 051
in Change-Point ARX Models and Robotics
Yuguo Chen, Tze Leung Lai and Bin Wu

5. An Adaptive Controller Design for Flexible-joint Electrically-driven Robots 071
With Consideration of Time-Varying Uncertainties
Ming-Chih Chien and An-Chyau Huang

6. Global Feed-forward Adaptive Fuzzy Control of Uncertain MIMO Nonlinear 097
Systems
Chian-Song Chiu and Kuang-Yow Lian

7. Function Approximation-based Sliding Mode Adaptive Control for 121
Time-varying Uncertain Nonlinear Systems
Shuang Cong, Yanyang Liang and Weiwei Shang

8. Model Reference Adaptive Control for Robotic Manipulation with Kalman 145
Active Observers
Rui Cortesão

9. Triggering Adaptive Automation in Naval Command and Control 165
Tjerk de Greef and Henryk Arciszewski

10. Advances in Parameter Estimation and Performance Improvement in 189
Adaptive Control
Veronica Adetola and Martin Guay
X
11. Estimation and Control of Stochastic Systems under Discounted Criterion 209
Hilgert Nadine and Minjárez-Sosa J. Adolfo

12. Lipschitzian Parameterization-Based Approach for Adaptive Controls of 223
Nonlinear Dynamic Systems with Nonlinearly Parameterized Uncer-
tainties: A Theoretical Framework and Its Applications
N.V.Q. Hung, H.D. Tuan and T. Narikiyo

13. Model-free Adaptive Control in Frequency Domain: 253
Application to Mechanical Ventilation
Clara Ionescu and Robin De Keyser

14. Adaptive Control Design for Uncertain and Constrained Vehicle Yaw 271
Dynamics
Nazli E. Kahveci

15. A Design of Discrete-Time Indirect Multivariable MRACS with Structural 281
Estimation of Interactor
Wataru Kase and Yasuhiko Mutoh

16. Adaptive Control in Wireless Networks 297
Thomas D. Lagkas, Pantelis Angelidis and Loukas Georgiadis

17. Adaptive Control Methodology 321
for High-performance Low-power VLSI Design
Se-Joong Lee