design and control of automatic finger by …
TRANSCRIPT
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
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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.