I. Ramos Arreguin (ed.) Automation and Robotics

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Automation and Robotics

Edited by

Juan Manuel Ramos Arreguin

I-Tech

Published by I-Tech Education and Publishing

I-Tech Education and Publishing

Vienna

Austria

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 I-Tech Education and Publishing, authors have the right to repub-

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First published May 2008

Printed in Croatia

A catalogue record for this book is available from the Austrian Library.

Automation and Robotics, Edited by Juan Manuel Ramos Arreguin

p. cm.

ISBN 978-3-902613-41-7

1. Automation. 2. Robotics. I. Ramos Arreguin

Preface

In this book, a set of relevant, updated and selected papers in the field of automation and

robotics are presented. These papers describe projects where topics of artificial intelligence,

modeling and simulation process, target tracking algorithms, kinematic constraints of the

closed loops, non-linear control, are used in advanced and recent research.

Also, the lecturer can find some of the new methodologies applied to solve complex

problems in the field of control and robotic research fields. Moreover, this book can serve as

a good information source for scientific scholars, engineers and beginners who would like to

start working with both automation and robotic areas. Combining the ideas of the diverse

disciplines involved in such areas, this book give hints and help about how to implement

them on products for industrial automation and robotics applications.

I would like to thank all the researchers who send their works to share with the scientific

community. The editors are extremely grateful to all of them for their support to complete

this book.

Editor

Juan Manuel Ramos Arreguin

Electronica y Automatizacion

Universidad Tecnologica de San Juan del Rio

jramos@mecamex.net

VII

Contents

Preface V

1. Tracking Control for Multiple Trailer Systems by Adaptive Algorithmic

Control

001

Tomoaki Kobayashi, Toru Yoshida, Junichi Maenishi, Joe Imae and Guisheng Zhai

2. Enhanced Motion Control Concepts on Parallel Robots 017

Frank Wobbe, Michael Kolbus and Walter Schumacher

3. Vision Guided Robot Gripping Systems 041

Zdzislaw Kowalczuk and Daniel Wesierski

4. Closed-Loop Feedback Systems in Automation and Robotics,

Adaptive and Partial Stabilization

073

G. R. Rokni Lamooki

5. Nonlinear Control Law for Nonholonomic Balancing Robot 087

Alicja Mazur and Jan Kdzierski

6. Deghosting Methods for Track-Before-Detect Multitarget

Multisensor Algorithms

097

Przemyslaw Mazurek

7. Identification of Dynamic Systems & Selection of Suitable Model 121

Mohsin Jamil, Dr. Suleiman M Sharkh and Babar Hussain

8. Towards an Automated and Optimal Design of Parallel Manipulators 143

Marwene Nefzi, Martin Riedel and Burkhard Corves

9. Identification of Continuous-Time Systems with Time Delays by

Global Optimization Algorithms and Ant Colony Optimization

157

Janusz P. Paplinski

10. Linear Lyapunov Cone-Systems 169

Przemysaw Przyborowski and Tadeusz Kaczorek

11. Pneumatic Fuzzy Controller Simulation vs Practical Results for

Flexible Manipulator

191

Juan Manuel Ramos-Arreguin, Jesus Carlos Pedraza-Ortega,

Efren Gorrostieta-Hurtado, Rene de Jesus Romero-Troncoso,

Jose Emilio Vargas-Soto and Francisco Hernandez-Hernandez1

VIII

12. Nonlinear Control Strategies for Bioprocesses: Sliding Mode

Control versus Vibrational Control

201

Dan Seliteanu, Emil Petre, Dorin Popescu and Eugen Bobau

13. Sliding Mode Observers for Rotational Robotics Structures 223

Dorin Sendrescu, Dan Seliteanu, Emil Petre and Cosmin Ionete

14. A Declarative Framework for Constrained Search Problems in

Manufacturing

243

Sitek Pawek and Wikarek Jaroslaw

15. Derivation and Calculation of the Dynamics of Elastic Parallel Manipulators 261

Krzysztof Stachera and Walter Schumacher

16. Orthonormal Basis and Radial Basis Functions in Modeling and

Identification of Nonlinear Block-Oriented Systems

277

Rafa Stanisawski and Krzysztof J. Latawiec

17. Control System of Underwater Vehicle Based on Artificial

Intelligence Methods

285

Piotr Szymak and Józef Maecki

18. Automatization of Decision Processes in Conflict Situations:

Modelling, Simulation and Optimization

297

Zbigniew Tarapata

19. Fuzzy Knowledge Representation Using Probability Measures of

Fuzzy Events

329

Anna Walaszek-Babiszewska

20. Multiple Multi-Objective Servo Design - Evolutionary Approach 343

Piotr Wozniak

21. Model-Based Control of a Nonlinear One Dimensional Magnetic

Levitation with a Permanent-Magnet Object

359

Zhenyu Yang, Gerulf K.M. Pedersen and Jørgen H. Pedersen

22. Nonlinear Adaptive Tracking-Control Synthesis for General Linearly

Parametrized Systems

375

Zenon Zwierzewicz

Tracking Control for Multiple Trailer Systems

by Adaptive Algorithmic Control

Tomoaki Kobayashi, Toru Yoshida, Junichi Maenishi,

Joe Imae and Guisheng Zhai

Osaka Prefecture University

Japan

1. Introduction

In recent years, a truck-trailer system is the most useful physical distribution system. The

truck-trailer systems have more convenience than coastal services or freight trains.

Meanwhile, problems of the traffic jam and the air pollution in an urban area have become

serious, year after year. Therefore improvement and rationalization of the transport

efficiency are social needs. There are many papers suggesting a platoon system of several

trucks as a part of development of ITS (Intelligent Transport System). These platoon systems

consist of several unmanned trucks automatically following a truck driven by a conductor,

and it is commonly believed that it brings improvements of energy efficiency along with

alleviation of the traffic jam. Moreover, there is a purpose of covering insufficient workforce

of truck drivers who have to do severe labors, too. In the platoon, trucks are not physically

connected to each other, and thus there is much flexibility. On the other hand, even if each

vehicle is physically connected by mechanical linkage, this is not important restrictions, for

transport robots which are operated in the factory, because moving range and action plan

are limited. Moreover, the multiple trailer system is safer than platoon system, because if

each vehicle is physically connected, there is no danger of collision among trailers. In this

paper, we deal with a control method for a physically connected multiple trailer robot,

which is a transport system in factories.

The control method of connected vehicle has been studied for a long time (Laumond, 1986).

In particular, there are many papers which studied controlling its backward motion with

guaranteed stability (Sampei & Kobayashi, 1994). Moreover, kinematical model of a multiple

trailer system is described by a nonholonomic system, and it is a controllable nonlinear

system (Hermann & Krener, 1977). In theoretical field, it has been a hot subject of research,

because asymptotic stabilization is impossible using one continuous time-invariant since the

nonholonomic system does not satisfy the Brockett's necessary condition for stabilizability

(Brockett, 1983). Therefore, the control problem of nonholonomic system is a theoretically

difficult problem, thereupon various researches such as time-variant controller (M'Closkey

& Murray, 1993) or hybrid control techniques (Matsune et al., 2005) are performed. We look

at this issue from more practical point of view, then investigate a real-time control

algorithm, which is based on the so called algorithmic control (Kobayashi et al., 2005a),

(Imae et al., 2005) with a similar formulation of the model predictive control (MPC)

Automation and Robotics

technique for nonlinear continuous time system. Our algorithmic design approach is a

technique for ensuring robustness by adopting a numeric solution called Riccati Equation

Based (REB) algorithm using quasi linearization that includes feedback solution. Moreover,

though details are described later, the control technique by algorithmic design which we

proposed is an effective method for nonholonomic systems because our method is switching

and applying the control strategy on a short control interval and thus the controller is

discontinuous time variant, which does not violate Brockett's theorem. We showed the

effectiveness of proposed method applicable to nonholonomic systems through some

simulations and an experiment with a differential-driven unicycle vehicle model (Kobayashi

et al., 2005b). Then, we extend our design method by incorporating numerical robustness for

disturbances and parameter uncertainties and, by focusing on the switching interval of

control strategy on iterative process of algorithmic design (Kobayashi et al., 2006). We

discussed about effectiveness of our approach for an unstable motion control of high order

nonlinear system, in this paper. In the most of conventional research, the direct-hooked type

model (Lee et al., 2001) is treated. The direct-hooked model can be transformed to a

canonical form called chained form (Murray & Sastry, 1993). Then, control problem for the

direct-hooked model can be reduced to a canonical problem. However, the direct-hooked

model has a tracking error of follow-on trailers (Fig.1). Therefore, there are many

suggestions for eliminating the tracking error by model constructions or mechanical linkage

design. We pick up a off-hooked model (Lee et al., 2004) which has a most simple structure

and cannot be converted to canonical form (Ishikawa, 1993). Therefore, proposed

algorithmic design is considered as an effective strategy for the off-hooked trailer system,

because our approach can treat the general nonlinear systems. The effectiveness is discussed

through a numerical simulation result.

The outline of this paper is as follows. In section 2, we describe the nonlinear optimal

control problems and the Riccati Equation Based algorithm. In section 3, the algorithmic

design method is described in detail. Also, we make an extension of our design method for

robustness. The backward motion control problem of multiple trailer systems is formulated

in section 4. In section 5, we show some simulation results in order to demonstrate the

effectiveness of adaptive algorithmic design. Section 6 concludes the paper.

ｖ

Tracking Error

Fig. 1 Tracking error of the direct-hooked trailer system

2. Optimal control problem

2.1 Formulation

We deal with the following general nonlinear system

() (, (), ())

tftxtut



(1)