Advances in Mechatronics Part 1 doc

Contents Preface IX Part 1 Automatic Control and Artificial Intelligence 1 Chapter 1 Integrated Control of Vehicle System Dynamics: Theory and Experiment 3 Wuwei Chen, Hansong Xiao,

ADVANCES IN  MECHATRONICS 

 

Edited by Horacio Martínez‐Alfaro 

 

 

 

 

 

 

 

 

 

 

 

Advances in Mechatronics

Edited by Horacio Martínez-Alfaro

Published by InTech

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Contents

 

Preface IX Part 1 Automatic Control and Artificial Intelligence 1

Chapter 1 Integrated Control of

Vehicle System Dynamics: Theory and Experiment 3

Wuwei Chen, Hansong Xiao, Liqiang Liu, Jean W Zu and HuiHui Zhou

Chapter 2 Integrating Neural Signal

and Embedded System for Controlling Small Motor 31

Wahidah Mansor, Mohd Shaifulrizal Abd Rani and Nurfatehah Wahy

Chapter 3 Artificial Intelligent Based Friction Modelling

and Compensation in Motion Control System 43

Tijani Ismaila B., Rini Akmeliawati and Momoh Jimoh E Salami Chapter 4 Mechatronic Systems for Kinetic Energy

Recovery at the Braking of Motor Vehicles 69

Corneliu Cristescu, Petrin Drumea, Dragos Ion Guta, Catalin Dumitrescu and Constantin Chirita

Chapter 5 Integrated Mechatronic Design

for Servo Mechanical Systems 109

Chin-Yin Chen, I-Ming Chen and Chi-Cheng Cheng

Part 2 Robotics and Vision 129

Chapter 6 On the Design of Underactuated

Finger Mechanisms for Robotic Hands 131

Pierluigi Rea Chapter 7 Robotic Grasping and Fine

Manipulation Using Soft Fingertip 155

Akhtar Khurshid, Abdul Ghafoor and M Afzaal Malik

VI Contents

Chapter 8 Recognition of Finger Motions for

Myoelectric Prosthetic Hand via Surface EMG 175

Chiharu Ishii Chapter 9 Self-Landmarking for Robotics Applications 191

Yanfei Liu and Carlos Pomalaza-Ráez Chapter 10 Robotic Waveguide by Free Space Optics 207

Koichi Yoshida, Kuniaki Tanaka and Takeshi Tsujimura Chapter 11 Surface Reconstruction of Defective

Point Clouds Based on Dual Off-Set Gradient Functions 223

Kun Mo and Zhoupin Yin

Part 3 Other Applications and Theory 245

Chapter 12 Advanced NO x Sensors for Mechatronic Applications 247

Angela Elia, Cinzia Di Franco, Adeel Afzal,

Nicola Cioffi and Luisa Torsi

Chapter 13 Transdisciplinary Approach of the

Mechatronics in the Knowledge Based Society 271

Ioan G.Pop and Vistrian Mătieş

   

Preface

 

The  community  of  researchers  claiming  the  relevance  of  their  work  to  the  field  of  mechatronics is growing faster and faster, despite the fact that the term itself has been 

in the scientific community for more than 40 years. Numerous books have been pub‐ lished  specializing  in  any  one  of  the  well  known  areas  that  comprised  it:  mechanical  engineering, electronic control and systems, but attempts to bring them together as a  synergistic integrated areas are scarce. Yet some common application areas clearly ap‐ pear since then. 

The goal of this book is to collect state‐of‐the‐art contributions that discuss recent de‐ velopments that show more more synergistic integration among the areas. The book is  divided in three sections with out and specific special order. The first section is about  Automatic Control and Artificial Intelligence with five chapters, the second section is  Robotics and Vision with six chapters, and the third section is Other Applications and  Theory with two chapters. 

The  first  chapter  on  Automatic  Control  and  Artificial  Intelligence  by  Wuwei  Chen,  Hansong Xiao, Liqiang Liu, Jean W. Zu, and HuiHui Zhou is some theory and experi‐ ments  of  integrated  control  vehicle  dynamics.  The  second  chapter  by  Wahidah  Mansor, Saifulrizal Ab Rani, and Nurfatehah Wahi is about integrating  neural signal  and  embedded  system  for  controlling  a  small  motor.  Ismaila  B.  Tijani,  Akmeliawati  Rini,  and  Jimoh  E.  Salami  Momoh  in  the  third  chapter  shows  an  artificial  intelligent  based  friction  modelling  and  compensation  for  motion  control  system.  The  fourth  chapter  by  Corneliu  Cristescu,  Petrin  Drumea,  Dragos  Ion  Guta,  and  Catalin  Dumi‐ trescu is about a mechatronic systems for kinetic energy recovery at the braking of mo‐ tor vehicles.  The fifth chapter and last of this section by Chin‐Yin Chen, I‐Ming Chen,  and  Chi‐Cheng  Cheng  is  about  integrated  mechatronic  design  for  servo‐mechanical  systems. 

For the Robotics and Vision section, the first chapter is on the design of underactuat‐

ed finger mechanisms for robotic hands by Pierluigi Rea. The following chapter by  Akhtar Khurshid deals with robotic grasping and fine manipulation using soft finger‐ tip. In the next chapter, Chiharu Ishii talks about recognition of finger motions for my‐ oelectric  prosthetic  hand  via  surface  EMG.  Yanfei  Liu  and  Carlos  Pomalaza‐Ráez  in  the following chapter talks about self‐landmarking for robotics applications. The next 

X Preface

chapter  is  about  robotic  waveguide  by  free  space  optics  by  Koichi  Yoshida,  Kuniaki  Tanaka, and Takeshi Tsujimura. And the last chapter for this section by Kun Mo and  Zhoupin  Yin  is  about  surface  reconstruction  of  defective  point  clouds  based  on  dual  off‐set gradient functions. 

For the Other Applications and Theory section, the first chapter by Angela Elia, Cinzia 

Di Franco, Adeel Afzal, Nicola Cioffi and Luisa Torsi is about advanced NOx sensors  for mechatronic applications. The last chapter but not the least by Ioan G.Pop and Vis‐ trian  Mătieş  is  about  a  transdisciplinary  approach  of  the  mechatronics  in  the  knowledge based society. 

I do hope you will find the book interesting and thought provoking. Enjoy! 

 

Horacio Martínez‐Alfaro 

Mechatronics and Automation Department,   Tecnológico de Monterrey, Monterrey,  

México  July 2011 

 

Part 1

Automatic Control and Artificial Intelligence

1

Integrated Control of Vehicle System Dynamics:

Theory and Experiment

Wuwei Chen1, Hansong Xiao2, Liqiang Liu1,

Jean W Zu2 and HuiHui Zhou1

1Hefei University of Technology,

2University of Toronto,

P R China Canada

1 Introduction

Modern motor vehicles are increasingly using active chassis control systems to replace traditional mechanical systems in order to improve vehicle handling, stability, and comfort These chassis control systems can be classified into the three categories, according to their motion control of vehicle dynamics in the three directions, i.e vertical, lateral, and longitudinal directions: 1) suspension, e.g active suspension system (ASS) and active body control (ABC); 2) steering, e.g electric power steering system (EPS) and active front steering (AFS), and active four-wheel steering control (4WS); 3) traction/braking, e.g anti-lock brake system (ABS), electronic stability program (ESP), and traction control (TRC) These control systems are generally designed by different suppliers with different technologies and components to accomplish certain control objectives or functionalities Especially when equipped into vehicles, the control systems often operate independently and thus result in a parallel vehicle control architecture Two major problems arise in such a parallel vehicle control architecture First, system complexity in physical meaning comes out to be a prominent challenge to overcome since the amount of both hardware and software increases dramatically Second, interactions and performance conflicts among the control systems occur inevitably because the vehicle motions in vertical, lateral, and longitudinal directions are coupled in nature To overcome the problems, an approach called integrated vehicle dynamics control was proposed around the 1990s (Fruechte et al., 1989) Integrated vehicle dynamics control system is an advanced system that coordinates all the chassis control systems and components to improve the overall vehicle performance including safety, comfort, and economy

Integrated vehicle dynamics control has been an important research topic in the area of vehicle dynamics and control over the past two decades Comprehensive reviews on this research area may refer to (Gordon et al., 2003; Yu et al., 2008) The aim of integrated vehicle control is to improve the overall vehicle performance through creating synergies in the use

of sensor information, hardware, and control strategies A number of control techniques have been designed to achieve the goal of functional integration of the chassis control systems These control techniques can be classified into two categories, as suggested by (Gordon et al., 2003): 1) multivariable control; and 2) hierarchical control Most control

Advances in Mechatronics

4

techniques used in the previous studies fall into the first category Examples include nonlinear predictive control (Falcone et al., 2007), random sub-optimal control (Chen et al.,

2006), robust H (Hirano et al., 1993), sliding mode (Li et al., 2008), and artificial neural networks (Nwagboso et al., 2002), etc In contrast, hierarchical control has not yet been applied extensively to integrated vehicle control system It is indicated by the relatively small volume of research publications (Gordon et al., 2003; Gordon, 1996; Rodic and Vukobratovie, 2000; Karbalaei et al., 2007; He et al., 2006; Chang and Gordon, 2007; Trächtler, 2004) In the studies, there are two types of hierarchical control architecture: two-layer architecture (Gordon et al., 2003; Gordon, 1996; Rodic and Vukobratovie, 2000; Karbalaei et al., 2007; He et al., 2006) and three-layer architecture (Chang and Gordon, 2007; Trächtler, 2004) For instance in (Chang and Gordon, 2007), a three-layer model-based hierarchical control structure was proposed to achieve modular design of the control systems: an upper layer for reference vehicle motions, an intermediate layer for actuator apportionment, and a lower layer for stand-alone actuator control

In the review of the past studies on integrated vehicle dynamics control, we address the following two aspects in this study First, hierarchical control has been identified as the more effective control technique compared to multivariable control In addition to improving the overall vehicle performance including safety, comfort, and economy, application of hierarchical control brings a number of benefits, among which: 1) facilitating the modular design of chassis control systems; 2) mastering complexity by masking the details of the individual chassis control system at the lower layer; 3) favoring scalability; and 4) speeding up development processes and reducing costs by sharing hardware (e.g sensors) Second, most of the research activities on this area were focused solely on simulation investigations There have been very few attempts to conduct experimental study to verify the effectiveness of those proposed integrated vehicle control systems However, the experimental verification is an essential stage in developing those integrated vehicle control systems in order to transfer them from R&D activities to series production

In this chapter, a comprehensive and intensive study on integrated vehicle dynamics control

is performed The study consists of three investigations: First, a multivariable control technique called stochastic sub-optimal control is applied to integrated control of electric power steering system (EPS) and active suspension system (ASS) A simulation investigation is performed and comparisons are made to demonstrate the advantages of the proposed integrated control system over the parallel control system Second, a two-layer hierarchical control architecture is proposed for integrated control of active suspension system (ASS) and electronic stability program (ESP) The upper layer controller is designed

to coordinate the interactions between the ASS and the ESP A simulation investigation is conducted to demonstrate the effectiveness of the proposed hierarchical control system in improving vehicle overall performance over the non-integrated control system Finally, a hardware-in-the-loop (HIL) experimental investigation is performed to verify the simulation results

2 System model

In this study, two types of vehicle dynamic model are established: a non-linear vehicle dynamic model developed for simulating the vehicle dynamics, and a linear 2-DOF reference model used for designing controllers and calculating the desired responses to driver’s steering input

Integrated Control of Vehicle System Dynamics: Theory and Experiment 5

2.1 Vehicle dynamic model

A vehicle dynamic model is established and the three typical vehicle rotational motions,

including yaw motion, pitch motion, and roll motion, are considered They are illustrated in

Fig 1(a), Fig 1(b), and Fig 1(c), respectively In the figures, we denote the front-right wheel,

front-left wheel, rear-right wheel, and rear-left wheel as wheel 1, 2, 3, and 4, respectively

The equations of motion can be derived as:

For yaw motion of sprung mass shown in Fig 1(a)

1 2 3 4

z z xz y y y y

I I a F F b F F (1) And the equations of motion in the longitudinal direction and the lateral direction can be

written as

1 2 3 4

m v v m h  F F F F f mg (2)

1 2 3 4

m v v m hF F F F (3) For pitch motion of sprung mass shown in Fig 1(b)

3 4 1 2

y z z z z

Ib F F a F F (4) And for roll motion of sprung mass shown in Fig 1(c)

2 3 1 4

x s y x z xz z s z z z z

Im v v h I  m gh F F F F d (5)

1

F

4

F

1

x

F

4

3

x

F

3

y

F



2

F

2

F

v y

x

v

a

b

.

.G

C

(a) (b) (c)

Fig 1 Three typical vehicle rotational motions: (a) yaw motion; (b) pitch motion; (c) roll

motion

We also have the equations for the vertical motions of sprung mass and unsprung mass

1 2 3 4

s s z z z z

m z F F F F (6)

ui ui ti gi ui zi

where

2 1

1 1( 1 1) 1( 1 1) [ ( )] 1

af u u

z s u s u s

        (8)