ii

DESIGN AND CONTROL OF AUTOMATIC FINGER

EXTENSOR BASED ON IRIS MECHANISM FOR HAND

REHABILITATION SYSTEM

BY

MUHAMMAD AMINUDDIN ANWAR BIN ALI

A thesis submitted in fulfilment of the requirement for the

degree of Master of Science (Mechatronics Engineering)

Kulliyyah of Engineering

International Islamic University Malaysia

MARCH 2019

ii

ABSTRACT

The impairment of motor function in stroke patients cause them to be paralysed. With

the extensive rehabilitation training and exercise, the probability for stroke patient to

regain movement is high. At early stage, most of the stroke patient cannot extend their

finger because of the weakness in the muscle. At this rate, their fingers are always in

flexed condition. The therapist has to extend their fingers to prevent the muscle

hardened. However, limitation of the therapist has become a crucial problem and with

the help from the robotic rehabilitation, the rehabilitation become easier and helpful.

Finger extensor can help the patients to perform the exercise precisely and repeatedly.

For finger extensor, the mechanism needs to provide variable diameter opening to

extend the fingers and the opening need to be controlled, so that it follows the desired

trajectory. This research focus on the development of an automatic finger extensor

based on iris mechanism and its controller based on Sliding Mode Control-Function

Approximation Technique (SMC-FAT) based adaptive control. Motion simulation

studies and Finite Element Analysis (FEA) has been conducted on the proposed

automatic finger extensor. The prototype of the iris mechanism has been fabricated and

the test shows that it has worked successfully as required. The formulation of a Sliding

Mode Control-Function Approximation Technique (SMC-FAT) based adaptive

controller for proposed automatic finger extensor based on iris mechanism has been

presented. In this research, the controller is able to cater friction uncertainty and external

force from the patients. In this research, friction uncertainty is solved using FAT

expression where FAT expression issued to represent the uncertainties. In FAT

methods, Radial Basis Function Neural Network (RBFNN) is used as the basis function.

The stability of the controller can be proven using Lyapunov function. Simulation test

and hardware experimental test using MATLAB, Simulink and Real Time Window

Target have been conducted to verify the effectiveness of the controller. In the

simulation, the results show that the controller successfully compensate the

uncertainties and external force with average Root Mean Square of 1.35 mm.

iii

خلاصة البحث

لكن وهم الشلل التام. ل الوظائف الحركية لدى مرضى السكتة الدماغية يسبب خللإن

لمرضى ا ةدستعاا تصبح احتمالية التمارين والتدريبات التأهيلية المكثفة،ممارسة مع

ماغية لا يستطي ةفي المرحل .عالية للحركة أن عون المبكرة، معظم مرضى السكتة الد

ناءالانثت الحركة. ولهذا تكون الأصابع في حالة ضعف عضلانظرا لأصابعهم يحركوا

لا إ. تصلب العضلاتالأصابيع لتجنب تحريكالمعالج ويجب علىولا يمكن تحريكها.

اعدة وبمس ،مشكلة حاسمةتجعل من المعالجة القيود التي تواجه المعالج الطبيعي أن

ستخدام فباة. فيدموأكثر سهولة تأهيل الإعادة عملية إعادة التأهيل أصبحت روبوتات

از ومتكرر. في جهدقيق بشكل التدريبات بلقيام يمكن للمرضى ا الأصبع اسطجهاز ب

يمكن وأنالأصبع بسطلة قطر متغيرفتحة ال تكونأن لية إلى الآتحتاج الأصبع باسطة

الباسطةويركز هذا البحث على تطوير . لمسار المطلوبا بحيث تتبع، التحكم بها

ساس جهاز التحكم يقوم على ألية القزحية والآعلى التي تعتمدالتلقائية للأصبع

Sliding Mode Control-Function Approximation Technique

(SMC-FAT) .الحركات ةمحاكاعلى دراساتال يتجروقد أ بناء على التحكم التكيفي

كيب تر وتم المقترحة.للأصبع لباسطة الآلية اعلى ( FEAالدقيقة )وتحليل العناصر

تم و طلوب.أنها تعمل بنجاح كما هو مب نتيجةال ظهرتلية القزحية وأللآ النموذج الأولي

Sliding Mode Control-Function Approximation صيغة تقديم

Technique (SMC-FAT) باسطة الآلية لحدة التحكم المتفاعلة لوعلى ةالمعتمد

لتحكم أن افي هذا البحث، تستطيع وحدة لية القزحية.الآ القائمة علىالمقترحة للأصبع

في هذا والقوى الخارجية لدى المرضى. وغير المتوقعة حتكاكات الاتغلب على ت

ل هذه الاحتكاكات باستخدام البحث، ةقاعد . وفيالغموضلتمثيل FATمصطلح تح

FAT، ستخدمي Radial Basis Function Neural Network أساسا للوظائف

ختبارإوأجري دالة ليابونوف. بوظيفة وحدة التحكماستقرار إثبات يمكن والأساسية.

Realوسيميولينك و برنامج ماتلاب باستخدام ختبار التجريبي للمعداتالاالمحاكاة و

Time Window Target وفي المحاكاة، أشارت . للتحقق من فعالية وحدة التحكم

ذر ج معدلض الغموض والقوى الخارجية بيتعو نجحت فيالتحكم وحدة أن النتائج إلى

.مليمترا 1.35 متوسط المربع بقيمة

iv

APPROVAL PAGE

I certify that I have supervised and read this study and that in my opinion; it conforms

to acceptable standards of scholarly presentation and is fully adequate, in scope and

quality, as a thesis for the degree of Master of Science (Mechatronics Engineering).

…………………………………….

Norsinnira Zainul Azlan

Supervisor

…………………………………….

Asan Gani bin Abdul Muthalif

Co-supervisor

I certify that I have read this study and that in my opinion it conforms to acceptable

standards of scholarly presentation and is fully adequate, in scope and quality, as a

thesis for the degree of Master of Science (Mechatronics Engineering).

…………………………………….

Siti Fauziah binti Toha@Tohara

Internal Examiner

…………………………………….

Ruhizan Liza Bt Ahmad Shauri

External Examiner

This thesis was submitted to the Department of Mechatronics Engineering and is

accepted as a fulfillment of the requirement for the degree of Master of Science

(Mechatronics Engineering).

…………………………………….

Syamsul Bahrin Abdul Hamid

Head, Department of Mechatronics

Engineering

This thesis was submitted to the Kulliyyah of Engineering and is accepted as a

fulfillment of the requirement for the degree of Master of Science (Mechatronics

Engineering)

…………………………………….

Ahmad Faris Ismail

Dean, Kuliyyah of Engineering

v

DECLARATION

I hereby declare that this thesis is the result of my own investigations, except otherwise

stated. I also declare that it has not been previously or concurrently submitted as a whole

for any other degrees at IIUM or other institutions.

Muhammad Aminuddin Anwar bin Ali

Signature...................................................

Date.........................................................

vi

INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA

DECLARATION OF COPYRIGHT AND AFFIRMATION OF

FAIR USE OF UNPUBLISHED RESEARCH

DESIGN AND CONTROL OF AUTOMATIC FINGER

EXTENSOR BASED ON IRIS MECHANISM FOR HAND

REHABILITATION SYSTEM

I declare that the copyright holder of this thesis are jointly owned by student and

International Islamic University Malaysia (IIUM).

Copyright © 2019 by Muhammad Aminuddin Anwar bin Ali and International Islamic University

Malaysia. All rights reserved.

No part of this unpublished research may be reproduced, stored in a retrieval system,

or transmitted, in any form or by any means, electronic, mechanical, photocopying,

recording or otherwise without prior written permission of the copyright holder

except as provided below

1. Any material contained in or derived from this unpublished research

may be used by others in their writing with due acknowledgement.

2. IIUM or its library will have the right to make and transmit copies (print

or electronic) for institutional and academic purposes.

3. The IIUM library will have the right to make, store in a retrieved system

and supply copies of this unpublished research if requested by other

universities and research libraries.

By signing this form, I acknowledged that I have read and understand the IIUM

Intellectual Property Right and Commercialization policy.

Affirmed by Muhammad Aminuddin Anwar bin Ali

……..…………………….. ………………………..

Signature Date

vii

ACKNOWLEDGEMENT

All praise to Allah (swt), for His blessing to give me inspiration, strength and revelation

to complete the research work fruitfully. I would like to express gratitude to Dr

Norsinnira binti Zainul Azlan for her assistance and encourage me wherever I faced

problem and complexity during the research. Besides that, I would like to show

appreciation to Assoc. Dr Asan Ghani bin Abdul Muthalif, who had assisted me to solve

the critical problem when I applied my controller to hardware.

I would like to thank my beloved father, Ali bin Alias and my late mother,

Salnah binti Ali together with my siblings whom constantly making prayer for me and

cherish me endlessly.

Last but not least, to all my friends, especially Intelligent Lab group, I want to

thank you for your support for me to complete this research.

viii

TABLE OF CONTENTS

Abstract .......................................................................................................................... ii

Abstract in Arabic ......................................................................................................... iii

Approval Page ............................................................................................................... iv

Declaration ..................................................................................................................... v

Copyright ...................................................................................................................... vi

Acknowledgements ...................................................................................................... vii

List of Tables ................................................................................................................. x

List of Figures ............................................................................................................... xi

List of Abbreviations .................................................................................................. xiii

List of Symbols ........................................................................................................... xiv

CHAPTER 1: INTRODUCTION ............................................................................... 1

1.1 Background .......................................................................................... 1

1.2 Problem Statement ............................................................................... 4

1.3 Research Objectives ............................................................................ 5

1.4 Research Methodology ........................................................................ 6

1.5 Contribution of the Research ............................................................... 9

1.6 Limitation and Scope of the Research ................................................. 9

1.7 Thesis Outline ...................................................................................... 9

CHAPTER 2: LITERATURE REVIEW ................................................................. 11

2.1 Introduction ....................................................................................... 11

2.2 Upper Limb Rehabilitation ................................................................ 11

2.2.1 Robotic Hand Device for Upper Limb Rehabilitation ................... 13

2.3 Iris Mechanism .................................................................................. 17

2.4 Control Strategies for Robotic Hand Devices in Upper Limb

Rehabilitation ................................................................................. 20

2.4.1 External Force ................................................................................ 20

2.4.2 Impedance Controller ..................................................................... 22

2.4.3 Admittance Controller .................................................................... 23

2.4.4 Adaptive Control and Sliding Mode Control (SMC) ..................... 25

2.4.5 SMC-FAT Based Adaptive Controller........................................... 26

2.5 Summary ............................................................................................ 29

CHAPTER 3: MECHANISM DESIGN ................................................................... 31

3.1 Introduction ....................................................................................... 31

3.2 Design of the Iris Mechanical ............................................................ 31

3.2.1 First Layer (Lower Body) .............................................................. 35

3.2.2 Blades ............................................................................................. 36

3.2.3 Second Layer (Incorporated with the Sprocket) ............................ 38

3.3 Finite Element Analysis (FEA) for the Pole ...................................... 40

3.4 Motion Simulation Studies ................................................................ 43

ix

3.5 Summary ............................................................................................ 44

CHAPTER 4: CONTROLLER DESIGN ................................................................ 45

4.1 Introduction ....................................................................................... 45

4.2 Kinematic Analysis of the Mechanism .............................................. 45

4.3 Dynamic Modelling of the Mechanism ............................................. 48

4.4 Actuator Dynamic Model .................................................................. 50

4.3.1 Integrated Dynamic Model with Actuator Dynamics .................... 53

4.4 Sliding Mode Controller with Function Approximation Technique

(SMC-FAT) based Adaptive Control ........................................... 57

4.5 Controller’s Stability Proof ............................................................... 61

4.6 Electrical Schematic .......................................................................... 63

4.6 RBFNN Basis Function for SMC-FAT based Adaptive Controller .. 67

4.7 Summary ............................................................................................ 69

CHAPTER 5: RESULTS AND DISCUSSION ....................................................... 70

5.1 Introduction ....................................................................................... 70

5.2 Iris Mechanism Prototype .................................................................. 70

5.3 Simulation Results of SMC-FAT based Adaptive Controller ........... 74

5.4 Experimental Results ......................................................................... 81

5.4 Summary ............................................................................................ 85

CHAPTER 6: CONCLUSION AND RECOMMENDATION .............................. 87

6.1 Conclusion ......................................................................................... 87

6.2 Recommendation and Future Work ................................................... 87

APPENDIX ................................................................................................................. 89

REFERENCES ........................................................................................................... 91

PUBLICATION ......................................................................................................... 96

x

LIST OF TABLES

Table 2.1 Summary of the robotic hand class 17

Table 3.1 Components and measurement 39

Table 4.1 Relation of iris mechanism 46

Table 4.2 Parameter for DC motor 51

Table 4.3 Input and output port 67

Table 5.1 Controllers parameters 77

Table 5.2 Summary of Simulation Results 81

Table 5.3 Parameter Control for Hardware 82

xi

LIST OF FIGURES

Figure 1.1 Bi-Manu-Track (Hesse et. al., 2015) 4

Figure 1.2 Flowchart Methodology 8

Figure 2.1

A. Rutgers Hand Master II, B. Reha-Digit, C. InMotion Hand

Robot, D, PneuGlove, E. Hand Wrist Assistive Rehabilitation

Device, F. Hand Exoskeleton Rehabilitation Robot (HEXORR)

(Lum et. al., 2012)

13

Figure 2.2 Iris valve (Mucon, 2017) 18

Figure 2.3

Table that uses iris mechanism (a) before rotation, (b) halfly

rotation

20

Figure 2.4 Reaction between external force, 𝐹𝑒𝑥𝑡 and robot 21

Figure 2.5 Implementation of impedance control (Ott et. al., 2010) 23

Figure 2.6 Admittance control (Ott et. al., 2010) 24

Figure 3.1 Iris mechanism components 32

Figure 3.2 Full design of iris mechanism (a) without casing, (b) with casing 34

Figure 3.3

Position of iris mechanism (a) and (b) initial state (closed) (c) and

(d) final state (fully opened)

35

Figure 3.4 Measurement for the first layer 35

Figure 3.5 Design of the blade 37

Figure 3.6 Top view (b) Bottom view of the blade 38

Figure 3.7 Blade travels for open and close 39

Figure 3.8 External force acting on the pole 41

Figure 3.9

FEA results of the 4.25 mm diameter pole when 10 N force applied

on it. (a) Von Mises values (b) URES changes when 10 N force

applied

43

Figure 3.10 Iris mechanism in 3D schematic 44

Figure 4.1 Iris mechanism arrangement 46

Figure 4.2 Graph between 𝜃2 and 𝑟𝑖𝑟𝑖𝑠 47

Figure 4.3 Iris mechanism with label 48

Figure 4.4 Free Body Diagram (FBD) of Iris mechanism 48

Figure 4.5 Sprocket first shaft and second shaft 52

Figure 4.6 Block diagram of the SMC- FAT based adaptive controller 61

xii

Figure 4.7 Prototype System Architecture 64

Figure 4.8 DC planet geared motor 65

Figure 4.9 Location of the encoder and torque sensor 65

Figure 4.10 NI-SCC 68 66

Figure 4.11 Structure of proposed RBF neural networks 68

Figure 5.1

Position of hand on fabricated iris mechanism (a) closed, (b) fully

extend

71

Figure 5.2 Experimental setup 72

Figure 5.3 Iris mechanism (a) front view (b) top view (c) isometric view 73

Figure 5.4 Movement of Iris mechanism 74

Figure 5.5 Simulation plant 76

Figure 5.6 Tracking performance when the external force is set to be 0 N 78

Figure 5.7 Tracking performance with external force, 2 N 78

Figure 5.8 Tracking performance with external force, 4 N 79

Figure 5.9 Tracking performance with external force, 6 N 79

Figure 5.10 Tracking performance with external force, 8 N 80

Figure 5.11 Tracking performance with external force, 10 N 80

Figure 5.12

Real Time Block Diagram of SMC-FAT based adaptive controller

(a) Overall block diagram (b) Encoder measurement

84

Figure 5.13 Hardware result 85

xiii

LIST OF ABBREVIATIONS

ADL Activity Daily Life

ASSIST Active Support Splint

CPM Continuous Passive Machine

DC Direct Current

DOF Degree of Freedom

EMG Electromyography

et. al. (et alia): and others

FAT Function Approximation Technique

FEA Finite Element Analysis

FM Fugl-Meyer

HEXORR Hand Exoskeleton Rehabilitation Robot

HWARD Hand Wrist Assistive Rehabilitation Device

PWD People with Disability

RBFN Radial Basis Function Network

RBFNN Radial Basis Function Neural Network

ROM Range of Motion

SMC Sliding Mode Control

WHO World Health Organization

xiv

LIST OF SYMBOLS

N Newton

mm Millimetre

Σ Summation

s Second

Nm Newton meter

1

CHAPTER 1

INTRODUCTION

1.1 BACKGROUND

The upper limb or upper extremity is the region in a vertebrate animal extending from

the deltoid region to the hand, including the arm, axilla and shoulder. Upper limb or

upper extremity is a complex part of the human body. It consists shoulder, elbow,

forearm, wrist, and fingers (Guo et. al., 2016). These parts consist of 27 degree of

freedom (DOF), where 7 is located within the shoulder, elbow, forearm, and wrist, while

another 21 DOF are located at the fingers.

Commonly, fingers are used to hold or grasp various size of objects such as

pencil, ball and glass. Besides that, fingers are very important for daily self-care such

as eating, drinking, working including typing on the keyboard, driving and performing

everyday activities such as playing sport and washing the clothes (Dollar, 2014).

Loss of hand function will affect human activities especially activities of daily

life (ADL). It prevents the patient from performing effective occupation. The disabled

with impaired hand need to rely on other person such as family members. According to

Department of Social Welfare Malaysia, in 2014, 531,962 people are registered as

people with disability (PWD). Among this people, 174,795 individuals are recorded as

having physical disability.

There are 2 main reasons contributing to the loss of hand function. First is

accident and second is stroke. According to World Health Organization (WHO), in

2011, more than a billion people or about 15% of the world’s population are estimated

2

to live with different form of disability (based on 2010 global population estimate).

Stroke is a neurological disease with the highest prevalence and a leading cause for

upper limb impairment (Nef, et. al., 2009). Most of the stroke patients suffer from

hemiparesis where they cannot control the movement of one side or whole body due to

the motor impairment (Basteris et. al., 2014). Common effects of motor function

impairment are muscle weakness, spasticity, increased reflexes, loss of coordination

and apraxia (Kelly-Hayes et. al., 1998; Wolfe, 2000; Teasell, 1991; Trombly, 1992).

One of the muscle weaknesses faced by stroke patients is the inability to extend

or flex the fingers by themselves. The muscle weakness is not uniform between the

extensor and flexor muscles (Chen et. al., 2002). The process for finger extension

requires several muscles to be activated and the inability to activate the muscle group

during extension can reduce the hand’s range of motion (ROM) (Kwakkel et. al., 2004).

Stroke survivors can regain the original flexion and extension functions of the hand by

undergoing rehabilitation therapy with the help of a therapist (Fu et. al., 2006).

Rehabilitation is a therapy that enables the people with disabilities to recover

their limbs function to perform activities of daily living (ADL), return to the community

and work, and participate in educational routines (WHO, 2014). It helps the patient to

prevent further consequences of disease or injury, reduce the use of health services and

improve quality of life (WHO, 2014). However, rehabilitation treatment involves

repetitive task, massed practice, task-oriented, re-education, and constraint-induced

movement therapy (Qian & Bi, 2014). Most of previous rehabilitation exercise are done

manually with one to one patient-therapist ratio. This will cause several limitations such

as labour-intensive and consume a lot of time and effort. The therapist can focus on one

patient at one time only. The hospital needs more therapist to assist the patients.

3

With the advance of technology and creativity, several rehabilitation devices or

machines, or robot-assisted systems have been developed to automate rehabilitation

treatment. With this, the therapist can handle or monitor more than 1 patient at one time.

The advantages of rehabilitation machines are it provides extra time for rehabilitation,

variety of exercises, and require minimum time to monitor patients (Qian & Bi, 2014).

Some of the examples of these types of systems developed for upper limb

rehabilitation systems include the Wearable Exotendon Networks (Park et. al., 2016),

twisted string actuation (TSA) (Hosseini et. al., 2017), Bio-Joint & Sensor (Jarret &

McDaid, 2017), Instrument Orthosis (Rosales et. al., 2015), MARIONET (Sulzer et. al.,

2007), ARM Guide (Allington et. al., 2000) and Manu Type (Chang & Kim, 2013).

Some of these rehabilitation robot focuses on specific movement only such as

MARIONET for the elbow, Active Support Splint (ASSIST) for the wrist (Sasaki et.

al., 2005), and CyberGrasp (Turner et. al., 1998) for the finger. On the other hand, a few

of them cater for the combination of several parts of the upper extremity such as ARM

Guide for the shoulder and elbow, Bi-Manu-Track as shown in the Figure 1.1 for the

forearm and wrist (Hesse et. al., 2003), and Gentle/G for the whole arm (Loureiro &

Harwin, 2007).

4

Figure 1.1 Bi-Manu-Track (Hesse et. al., 2015)

The hand rehabilitation system to automate the finger extension movement in

overcoming the affected motor function requires a mechanism that is capable of

providing variable-diameters opening motion. One of the mechanisms with this unique

feature is the iris mechanism. This type of mechanism is widely used in house furniture,

camera shutter and controlling liquid flow. For the house furniture, iris mechanism is

implemented in the dinner or round table design where the surface of the table expands

and enlarges after being rotated. The mechanism expands evenly under several rotations

from the center to produce various size of surface diameter. The iris mechanism is

designed to resist up to 10 N force from the patients where continuous passive motion

(CPM) and active motion can be performed. Besides that, the iris mechanism is chosen

because it is suitable for the disability patients to have training based on Modified

Ashworth Scale (MAS) and Fugl-Meyer (FM) motor assessment for upper limb

especially fingers.

This thesis focuses on the development and control of an automatic finger

extensor based on iris mechanism for hand rehabilitation system. The system provides

an automatic extension motion for the patient’s fingers.

1.2 PROBLEM STATEMENT

In some cases, the stroke patient’s hands are in flexed position at all times due

to affected muscle function. The therapist needs to use spline to extend patient’s fingers

or perform hand opening exercise repeatedly during rehabilitation (Hospital

Rehabilitasi Cheras, 2015). Most of the previous rehabilitation robot developed for

upper limb recovery are based on exoskeleton design. This type of system requires high

5

DOF and is difficult to be controlled especially for the fingers (Lum et. al., 2012). It is

bulky and mechanically complicated. Besides that, each finger needs to be attached to

every link in the mechanism which may cause serious injury (Maciejasz et. al., 2014).

Another problem with the existing exoskeleton based-rehabilitation system especially

for the fingers is the size is mainly made for the adults and less suitable for the children

due to the mechanical limitations.

Therefore, an automatic finger extensor to extends patient’s finger that

automatically extends the finger is necessary. The machine needs to be non-

exoskeleton-based design to prevent injury and accommodate users for all ages

including the children. The machine needs to be controlled, so that it follows the desired

extension motion. With this innovation and invention, it is targeted the disables and

stroke patients can regain the natural hand extension movement.

1.3 RESEARCH OBJECTIVES

The objectives of the research are as the following:

1. To design an automatic finger extensor mechanism for hand

rehabilitation based on iris mechanism.

2. To formulate the mathematical model of the automatic finger

extensor system for hand rehabilitation.

3. To develop the control algorithm in controlling the motion of the

automatic finger extensor for hand rehabilitation.

4. To evaluate the effectiveness proposed automatic finger extensor

system by simulation and experimental tests.

6

The proposed automatic extensor is required to provide extension motion to the finger

and follows the desired trajectory under the presence of the unknown friction and force

from the patient.

1.4 RESEARCH METHODOLOGY

The research methodology flowchart is shown in the Figure 1.2. The research

starts with the literature review on rehabilitation processes and mechanisms for the

fingers or hand. In this stage, the research focuses on identifying the potential new

design and suitable controller for the rehabilitation machine.

The next step is the design and development of the mechanical part the

rehabilitation system. Simple, portable, easy to use, and safety are the main concerns in

the design. The inner diameter, outer diameter and blade are calculated, so that the

proposed mechanism meets the design requirement.

The prototype is designed using the SolidWorks software. Finite Element

Analysis (FEA) is performed to obtain the correct size of the mechanism components

and motion analysis is done to check whether the design satisfies the design

requirement. After all requirements are satisfied, the model is developed into a

prototype and tested.

After that, the mathematical model of the proposed automatic finger extensor is

formulated and an adequate controller Sliding Mode Control (SMC) -Function

Approximation Technique (FAT) based adaptive controller for robotic hand device with

the influence of external force and unknown friction is developed. The performance of

the proposed controller is evaluated using MATLAB 2015 simulation. The controller

objective is satisfied if the error between the actual and desired trajectory is zero or very

close to zero.

7

After a satisfactory simulation result in tracking the desired trajectory is

achieved, the controller is tested on the robotic hardware. The experimental results are

compared with simulation results. When the both results are satisfactory, then the

research is documented in a full report.

8

Figure 1.2 Flowchart Methodology

9

1.5 CONTRIBUTION OF THE RESEARCH

The contributions of this research are as following:

1. A new automatic finger extensor based on iris mechanism for hand

rehabilitation.

2. Sliding Mode Controller with Function Approximation Technique

(SMC-FAT) based adaptive controller for the proposed automatic

finger extensor, under the presence of unknown fiction and force

exerted by the patient’s hand.

1.6 LIMITATION AND SCOPE OF THE RESEARCH

This study focuses on designing an automatic finger extensor based on iris

mechanism for hand rehabilitation. In this study, the friction is taken as the unknown

friction in the mathematical modelling of the proposed automatic finger extensor. Other

uncertainties are not considered in the mathematical modelling. Due to the mechanical

limitation based on the budget proposed, the external force exerted by the patients’ hand

is limited to 10 N force. The scope also only focuses on 10 N constant force. Higher

amount of constant force and the varying external force are beyond the scope of this

study.

1.7 THESIS OUTLINE

This thesis is organized into six chapters. The description of each chapter is given as

below:

10

An overview of the robotic hand device and rehabilitation robot is presented in Chapter

One. The problem statement, objectives, research methodology, contribution of the

research and the outline of this thesis are also presented.

Chapter Two provides the literature reviews on previous researches of hand

rehabilitation devices and machines. The controllers implemented in automatic upper

limb rehabilitation devices in the previous studies are also presented in this chapter.

Chapter Three describes the design of the automatic finger extensor based on iris

mechanism. All the important calculations in the design are calculated. The result of

Finite Element Analysis (FEA) of the automatic finger extensor device are also

presented. Besides that, the electrical components of the proposed system also have

been described in this chapter.

In Chapter Four, a dynamic model for the proposed 1-DOF automatic finger extensor,

its controller design based on SMC-FAT algorithm and the controller stability proof are

presented in detail.

In Chapter Five, the developed prototype of the automatic finger extensor system is

presented and the experimental setup is described. The simulation and experimental

results for the SMC-FAT based adaptive controller are also discussed in this chapter.

Finally, in Chapter Six conclusion and recommendation regarding the work are

presented.