Frontiers in Adaptive Control Part 1 pdf

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 formulati

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

Abstracting and non-profit use of the material is permitted with credit to the source Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher No responsibility is accepted for the accuracy of information contained in the published articles Publisher assumes no responsibility liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained inside After this work has been published by the In-Teh, authors have the right to republish it, in whole or part, in any publication of which they are an author or editor, and the make other personal use of the work

V

Preface

Starting in the early 1950s, the design of autopilots for high performance aircraft 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

moti-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 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

er-an unknown bounded disturber-ance 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 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

un-in adaptive control perspective: The design margun-ins un-in process and circuit level are 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

con-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-

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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 scong@ustc.edu.cn

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

in Change-Point ARX Models and Robotics

051

Yuguo Chen, Tze Leung Lai and Bin Wu

5 An Adaptive Controller Design for Flexible-joint Electrically-driven Robots

With Consideration of Time-Varying Uncertainties

071

Ming-Chih Chien and An-Chyau Huang

6 Global Feed-forward Adaptive Fuzzy Control of Uncertain MIMO Nonlinear

Systems

097

Chian-Song Chiu and Kuang-Yow Lian

7 Function Approximation-based Sliding Mode Adaptive Control for

Time-varying Uncertain Nonlinear Systems

121

Shuang Cong, Yanyang Liang and Weiwei Shang

8 Model Reference Adaptive Control for Robotic Manipulation with Kalman

Active Observers

145

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

Adaptive Control

189

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

Nonlinear Dynamic Systems with Nonlinearly Parameterized

Uncer-tainties: A Theoretical Framework and Its Applications

223

N.V.Q Hung, H.D Tuan and T Narikiyo

13 Model-free Adaptive Control in Frequency Domain:

Application to Mechanical Ventilation

253

Clara Ionescu and Robin De Keyser

14 Adaptive Control Design for Uncertain and Constrained Vehicle Yaw

Wataru Kase and Yasuhiko Mutoh

16 Adaptive Control in Wireless Networks 297

Thomas D Lagkas, Pantelis Angelidis and Loukas Georgiadis

17 Adaptive Control Methodology

for High-performance Low-power VLSI Design

321

Se-Joong Lee

1

An Adaptive Control for a Free-Floating Space

Robot by Using Inverted Chain Approach

Satoko Abiko and Gerd Hirzinger

Institute of Robotics and Mechatronics, German Aerospace Center (DLR)

Germany

1 Introduction

On-orbit servicing space robots are one of the challenging fields in the robotics and space technology The space robots are expected to perform various tasks including capturing a target, constructing a large structure and autonomous maintenance of on-orbit systems In these space missions, one of the main tasks with the robotic system would be the tracking, the grasping and the positioning of a target in operational space In this chapter, we address the task of following a desired trajectory in operational space while the space robot grasps a target with unknown dynamic properties The dynamic uncertainty leads to a tracking problem, where a given nominal trajectory has to be tracked, while accounting for the parameter uncertainty

In ground-based manipulator systems, the dynamic parameter uncertainty affects only dynamic equations In free-floating space robots, however, the parameter uncertainty appears not only in the dynamic equations but also in kinematic mapping from the joint space to the Cartesian space due to the absence of a fixed base Therefore, the model inaccuracies lead to the deviation of operational space trajectory provided by the kinematic mapping

One method to deal with this issue can be found in an adaptive control Xu and Gu proposed an adaptive control scheme for space robots in both joint space and operational space [Xu et al., 1992, Gu & Xu, 1993] However, the adaptive control proposed in [Xu et al., 1992] requires perfect attitude control and the adaptive control in [Gu & Xu, 1993] is developed based on an under-actuated system on the assumption that the acceleration of the base-satellite is measurable

In this chapter, we propose an adaptive control for a fully free-floating space robot in

operational space This chapter particularly focuses on the uncertainty of kinematic mapping, which includes the dynamic parameters of the system To achieve the desired input torque, it is assumed here that the velocity-based closed-loop servo controller is used

as noted in [Konno et al., 1997]

In the modeling of the space robot, we consider the system switched around since a floating space robot does not have any fixed base, and then the robotic system is modeled

free-from the end-effector to the base-satellite This approach was termed the inverted chain

approach in [Abiko et al., 2006] The inverted chain approach explicitly explains coupled

dynamics between the end-effector and the robot arm A proposed adaptive control for

Frontiers in Adaptive Control

2

operational space trajectory tracking is developed based on the inverted chain approach The control method is verified in simulation for a realistic three-dimensional scenario (See Fig 1)

The chapter is organized as follows Section 2 describes the dynamic model of a space robot

by the inverted chain approach Section 3 discusses the operational space motion control for the space robot based on the passivity theorem Section 4 proposes an adaptive control for trajectory tracking in operational space against parameter uncertainties Section 5 derives an alternative adaptive control for performance improvement Section 6 illustrates the simulation results with a three-dimensional realistic model The conclusions are summarized in Section 7

Figure 1 Chaser-robot and target scenario

2 Modeling and Equations of Motion

This section introduces the model of a space robot Since the focus of this research is on following a desired trajectory in operational space, it is convenient to refer to operational space formulation

Due to the lack of a fixed base, one can model a free-floating space robot with two approaches The general dynamic expressions of the free-floating robot use linear and angular velocities of the base-satellite and the motion rate of each joint as the generalized coordinates [Xu & Kanade, 1993] However, by considering the system switched around, modeled from the end-effector to the base, it can be represented by the motion of the end