Enhanced-PID Control Based Antagonistic Control For Pneumatic Artificial Muscle Actuators.

Faculty of Electrical Engineering

ENHANCED-PID CONTROL OF ANTAGONISTIC

PNEUMATIC ARTIFICIAL ACTUATED SYSTEM

Tan Ming Hui

Master of Science in Mechatronics Engineering

ENHANCED-PID CONTROL BASED ANTAGONISTIC CONTROL FOR PNEUMATIC ARTIFICIAL MUSCLE ACTUATORS

TAN MING HUI

A thesis submitted

in fulfillment of the requirements for the degree of Master of Science in Mechatronics Engineering

Faculty of Electrical Engineering

UNIVERSITY TEKNIKAL MALAYSIA MELAKA

DECLARATION

I declare that this thesis entitled “Enhanced-PID Control of Antagonistic Pneumatic Artificial Actuated System” is the result of my own research except as cited in the references. The thesis has not been accepted for any degree and is not concurrently submitted in candidature of any other degree.

Signature : ………...

Name : TAN MING HUI

APPROVAL

I hereby declare that I have read this thesis and in my opinion this thesis is sufficient in terms of scope and quality for the award of Master of Science in Mechatronics Engineering.

Signature : ………... Supervisor Name : ASSOC. PROF. DR. CHONG SHIN HORNG Date : ………...

DEDICATION

i ABSTRACT

Pneumatic artificial muscle (PAM) is a rubber tube clothed with a sleeve made of twisted fiber-code, and is fixed at both ends by fixture. It has a property like a spring, which enables it to change its own compliance by the inner air pressure. The advantages of pneumatic system such as high power-to-weight ratio, compactness, ease of maintenance, inherent safety and cleanliness led to the development of McKibben muscle and PAM actuators. However, the drawbacks of PAM, for example, the air compressibility and the lack of damping ability of PAM bring dynamic delay to the pressure response and cause oscillatory motion to occur. It is not easy to realize the PAM motion with high accuracy and high speed due to all the non-linear characteristics of pneumatic mechanism. In this thesis, an antagonistic-based PAM system is designed and presented. Two identical PAM actuators are connected in parallel and vertical direction which imitate the human biceps-triceps system and emphasize the analogy between the artificial muscle and human skeletal muscle behavior. Some past control algorithms on the positioning control of PAM mechanisms are discussed. In this thesis, a practical control method, namely enhanced-PID controller is proposed to control the trajectory motion of the PAM actuators. The development and modeling of the experiment setup are explained, followed by the driving characteristics of the PAM system. Two simple and straight forward steps are demonstrated as the design procedures of the enhanced-PID controller. The control structure of the proposed controller consists of a PID element, Compensator A and Compensator B. The effectiveness of the proposed control algorithm is validated in sinusoidal continuous motion. The tracking performance of the enhanced-PID controller is compared with a classic PID controller, showing that the control performance of the enhanced-PID controller is satisfactory and better in dealing with highly non-linear PAM system.

ii ABSTRAK

Otot tiruan pneumatik (PAM) merupakan sejenis tiub getah dengan lengan yang diperbuat daripada kod serat, dan ditetapkan pada kedua-dua perlawanan hujung. Ia mempunyai ciri seperti spring, yang membolehkannya menukar pematuhan sendiri dengan tekanan udara dalaman. Kelebihan sistem pneumatik seperti kuasa tinggi kepada nisbah berat badan, kompak, kemudahan penyelenggaraan, keselamatan dan kebersihan yang wujud membawa kepada pembangunan otot McKibben dan penggerak PAM. Walau bagaimanapun, kelemahan PAM, sebagai contohnya kebolehmampatan udara dan kekurangan redaman keupayaan PAM membawa kelewatan dinamik kepada tindak balas tekanan angin dan seterusnya menyebabkan gerakan ayunan berlaku. Memang adalah tidak mudah untuk merealisasikan gerakan PAM dengan ketepatan dan kelajuan yang tinggi disebabkan oleh semua ciri-ciri bukan linear mekanisme pneumatik. Dalam tesis ini, sistem PAM yang bertentangan telah direka dan dibentangkan. Dua batang penggerak PAM yang sama disambungkan dalam arah selari dan tegak supaya meniru sistem bisep-trisep manusia serta menekankan analogi antara otot tiruan dan tingkah laku otot rangka manusia. Beberapa algoritma kawalan lama yang menekankan kawalan kedudukan mekanisme PAM telah dibincangkan. Dalam tesis ini, satu kaedah kawalan yang praktikal, iaitu pengawal peningkatan PID telah dicadangkan untuk mengawal gerakan trajektori dari penggerak PAM. Pembangunan dan pemodelan persediaan eksperimen telahpun diterangkan, diikuti oleh ciri-ciri memandu sistem PAM. Sebanyak dua langkah mudah sahaja yang diperlukan telah ditunjukkan sebagai prosedur reka bentuk pengawal peningkatan PID. Struktur kawalan pengawal yang dicadangkan terdiri daripada elemen PID, pemampas A dan pemampas B. Keberkesanan algoritma kawalan yang dicadangkan tersebut disahkan dalam eksperimen berasaskan gerakan berterusan sinusoidal. Prestasi pengesanan pengawal peningkatan PID telah dibandingkan dengan pengawal PID klasik, menunjukkan bahawa prestasi kawalan pengawal peningkatan PID adalah memuaskan dan lebih baik dalam menangani sistem PAM yang tidak linear.

iii

ACKNOWLEDGEMENTS

First and foremost, I would like to take this opportunity to express my sincere acknowledgement to my supervisor, Dr. Chong Shin Horng from the Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka (UTeM) for her essential supervision, support and encouragement towards the completion of this thesis.

I would also like to express my greatest gratitude to Dr. Ahmad Zaki bin Shukor from Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka (UTeM), co-supervisor of this research for his advice and suggestions. Particularly, I would like to express my deepest gratitude to all lab members from Motion Control Research Lab (MCRL) for their assistant and efforts in all the lab and analysis works.

Special thanks to Zamalah scholarship, Universiti Teknikal Malaysia Melaka (UTeM) for the financial support throughout this project.

Last but not least, I would like to thank my family and friends for their moral support in completing this degree. Thank you to everyone who had been associated to the crucial parts of realization of this project.

iv

TABLE OF CONTENTS

PAGE DECLARATION

APPROVAL DEDICATION

ABSTRACT i

ABSTRAK ii

ACKNOWLEDGEMENTS iii

TABLE OF CONTENTS iv

LIST OF TABLES vi

LIST OF FIGURES vii

LIST OF APPENDICES xi

LIST OF ABBREVIATIONS xii

LIST OF SYMBOLS xiv

LIST OF PUBLICATIONS xvi

CHAPTER

1. INTRODUCTION 1

1.1 Introduction 1

1.2 Problem Statements 3

1.3 Objectives 3

1.4 Scope of Research 4

1.5 Significant of Study 4

1.6 Thesis Outline 5

2. LITERATURE REVIEW 6

2.1 Introduction 6

2.2 Human Arm Muscle 6

2.3 Pneumatic Artificial Muscle (PAM) 7

2.4 Control Methods for PAM Systems 11

2.4.1 Classical Controller 12

2.4.2 Model Based Controller 14

2.4.3 Intelligent Controller 21

2.4.4 Hybrid Control Method 26

2.5 PID Controller Concept 38

2.6 Ziegler Nichols Closed-Loop Tuning Method 40

2.7 Summary 41

3. METHODOLOGY 44

3.1 Introduction 44

3.2 Development and Modeling of PAM 44

3.2.1 Development of Antagonistic Based PAM System 45 3.2.2 Modeling of Antagonistic Based PAM System 52

3.3 Driving Characteristics of PAM 57

3.4 Enhanced PID Controller 62

3.4.1 Controller Concept 63

3.4.2 Design Procedure 66

v

4. RESULTS AND DISCUSSION 71

4.1 Introduction 71

4.2 Tracking Performance 73

4.3 Robustness Performance 94

4.4 Summary 106

5. CONCLUSIONS AND RECOMMENDATIONS FOR

FUTURE WORK 108

5.1 Introduction 108

5.2 Attainment of Research Objectives 108

5.3 Recommendations of Future Work 112

REFERENCES 113

vi

LIST OF TABLES

TABLE TITLE PAGE

2.1 Comparison between electric-driven, hydraulic and pneumatic artificial muscle actuators

9

2.2 Summary of past proposed control methods for PAM system 42

3.1 List of components model used 50

3.2 Estimated PID parameters 67

3.3 Fine-tuned PID parameters 67

4.1 Controller gains of the PID elements in two control systems 72 4.2 List of conducted experiments for tracking performance 73 4.3 �� � of the uncompensated system, classic PID controller and

enhanced-PID controller with variation of reference input and frequency

91

4.4 Experimental tracking results of 10 times repeatability 92 4.5 List of conducted experiments for robustness evaluation 94

vii

LIST OF FIGURES

FIGURE TITLE PAGE

2.1 FESTO pneumatic artificial muscle actuator 8

2.2 Control methods for PAM system 12

3.1 Human arm muscle structure (Grando and Mir, 2014) 46 3.2 Dimension of antagonistic-based PAM mechanism in SolidWorks

drawing

46

3.3 Fabricated steel base connected with two PAM actuators 47

3.4 Micro-box 2000 (TeraSoft Inc., 2012) 48

3.5 Schematic diagram of antagonistic-based PAM system 49 3.6 Photograph of experiment setup of antagonistic-based PAM system 50

3.7 Interfacing between PC and mechanism 51

3.8 Free body diagram of antagonistic based PAM system 52 3.9 Schematic diagram of antagonistic based PAM system 53

3.10 Side view of PAM mechanism 57

3.11 Static relationship between output rotation angle and input voltage 59 3.12 Static relationship between rotation angle and pressure 60 3.13 Static relationship between input voltage of PMA and pressure 61

3.14 Block diagram of enhanced PID controller 64

3.15 Step input open-loop experiment at amplitude of 20° 67

viii

4.2 Comparative results between classic PID and enhanced-PID for gains tuning

72

4.3 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 0.1 Hz)

75

4.4 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.1 Hz)

76

4.5 � versus amplitude of reference input angle at frequency of 0.1 Hz

77

4.6 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 0.2 Hz)

79

4.7 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.2 Hz)

80

4.8 � versus amplitude of reference input angle at frequency of 0.2 Hz

81

4.9 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 0.5 Hz)

83

4.10 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.5 Hz)

84

4.11 � versus amplitude of reference input angle at frequency of 0.5 Hz

85

4.12 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 1.0 Hz)

87

4.13 Comparative experimental tracking results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 1.0 Hz)

ix

4.14 � versus amplitude of reference input angle at frequency of 1.0 Hz

89

4.15 Graph of versus amplitude for 10-time repeatability test 93 4.16 Comparative experimental robustness results of the enhanced-PID

and classic PID controls for sinusoidal input (5°, 0.1 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

95

4.17 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.1 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

96

4.18 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 0.2 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

98

4.19 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.2 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

99

4.20 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 0.5 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

101

4.21 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 0.5 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

102

4.22 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (5°, 1.0 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

x

4.23 Comparative experimental robustness results of the enhanced-PID and classic PID controls for sinusoidal input (17°, 1.0 Hz) with weight of (a) 0 kg (b) 4 kg (c) 8 kg

xi

LIST OF APPENDICES

APPENDIX TITLE PAGE

A SolidWorks drawing for the antagonistic based PAM system 110 B Mathematical equation for Ziegler-Nichols second tuning

method

xii

LIST OF ABBREVIATIONS

ABBREVIATION DETAIL

ADC - Analogue to digital converter

AN-PID - Advanced Nonlinear Proportional-Integral-Derivative ARC - Adaptive Robust Control

DAC - Digital to analogue converter DAQ - Data acquisition unit

DOB - Disturbance Observer

DOF - Degree-of-freedom

DSC - Dynamic Surface Control

GA - Genetic Algorithm

GPIO - General-purpose input/output

I/O - Input/Output

ISAC - Intelligent Soft Arm Control

IPPSC - Intelligent Phase Plane Switching Control

LMS - Least Mean Square

LSE - Least Square Error

LVQNN - Learning Vector Quantization Neural Network MGA - Modified Genetic Algorithm

MRB - Magneto-Rheological Brake MRLS - Modified Recursive Least Square

xiii

MVC - Minimum Variance Control

NARX - Non-linear Autoregressive with Exogenous input NDOBC - Non-linear Disturbance Observer Based Control

NDOBDSC - Non-linear Disturbance Observer Based Dynamic Surface Control

PAM - Pneumatic Artificial Muscle

PC - Personal computer

PD - Proportional-Derivative

PID - Proportional-Integral-Derivative PMA - Pneumatic Muscle Actuator PPSC - Phase Plane Switching Control

SMC - Sliding Mode Control

SMCBNDO - Sliding Mode Control Based on Non-linear Disturbance Observer

SOM - Self-organizing Map

xiv

LIST OF SYMBOLS

SYMBOL DETAIL

a - Amount of inflation a0 - Initial braided angle

b - Amount if deflation

B1 - Damping coefficient for PMA 1

B2 - Damping coefficient for PMA 2

D - Depth

D0 - Initial muscle diameter

ε - Length ratio of muscle

e - Error

Emax - Maximum peak error

Epercent - Percentage of error

Erms - Root mean square of error

f - Frequency

H - Height

J - Moment of inertia

K1 - Spring coefficient for PMA 1

K2 - Spring coefficient for PMA 2

Kd - Derivative gain

xv Kp - Proportional gain

Ku - Ultimate gain

L0 - Initial muscle length

P - Input pressure

P0 - Nominal constant pressure

Pu - Ultimate period

Δp - Pressure difference

r - Radius

T - Rotating torque Td - Derivative time

Ti - Integral time θ - Rotational angle θr - Reference input angle

UA - Signal after PID controller

UB - Signal after Compensator A

U - Control voltage

xvi

LIST OF PUBLICATIONS

JOURNAL

1. Tan, M.H., Chong, S.H., Tang, T.F., Shukor, A.Z., Sakthivelu, V., Ma, T.C., and

Nawawi, M.R.Md., 2016. Tracking Control of Vertical Pneumatic Artificial Muscle

System Using PID. Journal of Telecommunication, Electronic and Computer

Engineering (JTEC) – Special Issue in Pioneering Future Innovation Through Green Technology, to be published.

2. Tang, T.F., Chong, S.H., Tan, M.H., Chan, C.Y., and Sato, K., 2016.

Characterization of Pneumatic Artificial Muscle System in an Opposing Pair

Configuration. Journal of Telecommunication, Electronic and Computer

Engineering (JTEC) – Special Issue in Pioneering Future Innovation Through Green Technology, to be published.

3. Sakthivelu, V., Chong, S.H., Tan, M.H., and Md Ghazaly, M., 2016.

Phenomenological Modeling and Classic Control of a Pneumatic Muscle Actuator

System. International Journal of Control and Automation (IJCA), 9 (4), pp.301-312.

CONFERENCE

1. Tan, M.H., Chong, S.H., Tang, T.F., Shukor, A.Z., Sakthivelu, V., Ma, T.C., and

Nawawi, M.R.Md., 2016. Tracking Control of Vertical Pneumatic Artificial Muscle

System Using PID. The 4th _{International Conference on Engineering and ICT (ICEI}

xvii

2. Tang, T.F., Chong, S.H., Tan, M.H., Chan, C.Y., and Sato, K., 2016.

Characterization of Pneumatic Artificial Muscle System in an Opposing Pair Configuration. The 4th _{International Conference on Engineering and ICT (ICEI} 2016).

3. Tan, M.H., Chong, S.H., Tang, T.F., and Shukor, A.Z., 2016. PID control of vertical

pneumatic artificial muscle system. In: Proceedings of Mechanical Engineering

1 CHAPTER 1

INTRODUCTION

1.1 Introduction

The human science and technology are getting more advanced as the world is moving forward. Machines and robots are created in order to replace human power. This is because the developed machineries are able to conduct complex work load in a shorter time and more safe condition as compared to the work being carried out by the human being. The motions of machines and robots rely on their own actuation systems as they function in providing forces, torque or any form of mechanical motion to the system in order to move.

There are three major groups of actuators or mechanisms applied to power motion control, such as electric-driven electro-mechanics, hydraulic and pneumatic. Electric system is commonly used as the actuator technology for most of the robotic applications nowadays. The advantages such as easy to use, simplicity, low cost and so on cause electric system to be widely used and applied on actuation system for the machines. However, electric actuator system suffers from the disadvantage of low to-weight ratio. Due to the low power-to-weight ratio of electric actuator system as compared to hydraulic and pneumatic systems, some industries prefer to use hydraulic or pneumatic systems as their machine actuator. However, pneumatic system is more preferable than hydraulic system by the industrial. The major advantages of pneumatic systems are their compactness, low cost, east of maintenance, and high power-to-weight ratio characteristic as compared to that of electric and hydraulic system. Therefore, these advantages have led to the development of novel actuator such as McKibben muscle or Pneumatic Artificial Muscle (PAM).

2

PAM has several advantages over conventional pneumatic cylinders, such as high force-to-weight ratio, flexibilities in installation and lower compressed air. However, difficulties arise when dealing with the modeling controllers for high positioning performance of PAM systems due to their highly nonlinear performance which results from compressibility of the air. As a result, a controller is necessary needed to help in achieving high positioning performance, stability and robustness in the system.

Up to now, various control methods have been designed and evaluated for PAM mechanisms. These proposed control methods can be categorized as classical control, intelligent control and model-based control. The conventional proportional-integral-derivative (PID) control is a classical controller that utilizes model-free control algorithms, including a feedback control action u(t) that utilizes the sum of three control parameters. PID controller is still a control approach that widely used in industrial due to its simplicity in structure and design procedure. With the appropriate selection of the three control parameters, the PID control can achieve the desired output and achieve the effectiveness.

In this research, an enhanced-PID controller based antagonistic control for PAM is proposed. The design and constructed PAM mechanism consists of two parallel PAM that provide a rotational antagonistic motion. It is a biologically inspired configuration that commonly applied in a therapy robot and as a breaking system in the industrial area. The effectiveness of the proposed controller is evaluated experimentally in tracking motion with various amplitudes and frequencies.

xiv

LIST OF SYMBOLS

SYMBOL DETAIL

a - Amount of inflation a0 - Initial braided angle b - Amount if deflation

B1 - Damping coefficient for PMA 1 B2 - Damping coefficient for PMA 2

D - Depth

D0 - Initial muscle diameter ε - Length ratio of muscle

e - Error

Emax - Maximum peak error Epercent - Percentage of error

Erms - Root mean square of error

f - Frequency

H - Height

J - Moment of inertia

K1 - Spring coefficient for PMA 1 K2 - Spring coefficient for PMA 2 Kd - Derivative gain

xv Kp - Proportional gain

Ku - Ultimate gain L0 - Initial muscle length P - Input pressure

P0 - Nominal constant pressure Pu - Ultimate period

Δp - Pressure difference

r - Radius

T - Rotating torque Td - Derivative time Ti - Integral time θ - Rotational angle θr - Reference input angle UA - Signal after PID controller UB - Signal after Compensator A U - Control voltage

xvi

LIST OF PUBLICATIONS

JOURNAL

1. Tan, M.H., Chong, S.H., Tang, T.F., Shukor, A.Z., Sakthivelu, V., Ma, T.C., and

Nawawi, M.R.Md., 2016. Tracking Control of Vertical Pneumatic Artificial Muscle System Using PID. Journal of Telecommunication, Electronic and Computer Engineering (JTEC) – Special Issue in Pioneering Future Innovation Through Green Technology, to be published.

2. Tang, T.F., Chong, S.H., Tan, M.H., Chan, C.Y., and Sato, K., 2016.

Characterization of Pneumatic Artificial Muscle System in an Opposing Pair Configuration. Journal of Telecommunication, Electronic and Computer Engineering (JTEC) – Special Issue in Pioneering Future Innovation Through Green Technology, to be published.

3. Sakthivelu, V., Chong, S.H., Tan, M.H., and Md Ghazaly, M., 2016.

Phenomenological Modeling and Classic Control of a Pneumatic Muscle Actuator System. International Journal of Control and Automation (IJCA), 9 (4), pp.301-312.

CONFERENCE

1. Tan, M.H., Chong, S.H., Tang, T.F., Shukor, A.Z., Sakthivelu, V., Ma, T.C., and

Nawawi, M.R.Md., 2016. Tracking Control of Vertical Pneumatic Artificial Muscle System Using PID. The 4th _{International Conference on Engineering and ICT (ICEI}

xvii

2. Tang, T.F., Chong, S.H., Tan, M.H., Chan, C.Y., and Sato, K., 2016.

Characterization of Pneumatic Artificial Muscle System in an Opposing Pair Configuration. The 4th _{International Conference on Engineering and ICT (ICEI}

2016).

3. Tan, M.H., Chong, S.H., Tang, T.F., and Shukor, A.Z., 2016. PID control of vertical

pneumatic artificial muscle system. In: Proceedings of Mechanical Engineering Research Day 2016. pp.206-207.

1 CHAPTER 1

INTRODUCTION

1.1 Introduction

The human science and technology are getting more advanced as the world is moving forward. Machines and robots are created in order to replace human power. This is because the developed machineries are able to conduct complex work load in a shorter time and more safe condition as compared to the work being carried out by the human being. The motions of machines and robots rely on their own actuation systems as they function in providing forces, torque or any form of mechanical motion to the system in order to move.

There are three major groups of actuators or mechanisms applied to power motion control, such as electric-driven electro-mechanics, hydraulic and pneumatic. Electric system is commonly used as the actuator technology for most of the robotic applications nowadays. The advantages such as easy to use, simplicity, low cost and so on cause electric system to be widely used and applied on actuation system for the machines. However, electric actuator system suffers from the disadvantage of low to-weight ratio. Due to the low power-to-weight ratio of electric actuator system as compared to hydraulic and pneumatic systems, some industries prefer to use hydraulic or pneumatic systems as their machine actuator. However, pneumatic system is more preferable than hydraulic system by the industrial. The major advantages of pneumatic systems are their compactness, low cost, east of maintenance, and high power-to-weight ratio characteristic as compared to that of electric and hydraulic system. Therefore, these advantages have led to the development of novel actuator such as McKibben muscle or Pneumatic Artificial Muscle (PAM).

2

PAM has several advantages over conventional pneumatic cylinders, such as high force-to-weight ratio, flexibilities in installation and lower compressed air. However, difficulties arise when dealing with the modeling controllers for high positioning performance of PAM systems due to their highly nonlinear performance which results from compressibility of the air. As a result, a controller is necessary needed to help in achieving high positioning performance, stability and robustness in the system.

Up to now, various control methods have been designed and evaluated for PAM mechanisms. These proposed control methods can be categorized as classical control, intelligent control and model-based control. The conventional proportional-integral-derivative (PID) control is a classical controller that utilizes model-free control algorithms, including a feedback control action u(t) that utilizes the sum of three control parameters. PID controller is still a control approach that widely used in industrial due to its simplicity in structure and design procedure. With the appropriate selection of the three control parameters, the PID control can achieve the desired output and achieve the effectiveness.

In this research, an enhanced-PID controller based antagonistic control for PAM is proposed. The design and constructed PAM mechanism consists of two parallel PAM that provide a rotational antagonistic motion. It is a biologically inspired configuration that commonly applied in a therapy robot and as a breaking system in the industrial area. The effectiveness of the proposed controller is evaluated experimentally in tracking motion with various amplitudes and frequencies.