Optimization of Industrial Systems
Description
Including the latest industrial solution-based practical applications, this is the most comprehensive and up-to-date study of the optimization of industrial systems for engineers, scientists, students, and other professionals.
In order to deal with societal challenges, novel technologies play an important role. For the advancement of technology, it is essential to share innovative ideas and thoughts on a common platform where researchers across the globe meet together and revitalize their knowledge and skills to tackle the challenges that the world faces. The high complexity of the issues related to societal interdisciplinary research is the key to future revolutions. From research funders to journal editors, policymakers to think tanks, all seem to agree that the future of research lies outside disciplinary boundaries. In such prevailing conditions, various working scenarios, conditions, and strategies need to be optimized.
Optimization is a multidisciplinary term, and its essence can be inculcated in any domain of business, research, and other associated working dynamics. Globalization provides all-around development, and this development is impossible without technological contributions. This volume's mission is at the core of industrial engineering. All the manuscripts appended in this volume were double-blind peer-reviewed by committee members and the review team, promising high-quality research. This book provides deep insights to its readers about the current scenarios and future advancements of industrial engineering.
Dilbagh Panchal, PhD, is an assistant professor in the Department of Industrial and Production Engineering, Dr. B R Ambedkar National Institute of Technology Jalandhar, Punjab, India. He earned his PhD from the Indian Institute of Technology Roorkee, India. He has published 22 research papers in scientific journals, ten book chapters in various books, and he has edited two books. He is a reviewer for several scientific journals, and he is currently working on seven books, including books for Scrivener Publishing.
Mohit Tyagi, PhD, is an assistant professor in the Department of Industrial and Production Engineering at Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India. He earned his PhD from the Indian Institute of Technology, Roorkee, India, and he has over seven years of teaching and research experience. He has roughly 75 publications in scientific journals and has numerous conference proceedings and book chapters to his credit. He is a reviewer for many technical journals and has organized three international conferences.
Anish Sachdeva, PhD, is an associate professor in the Department of Industrial and Production Engineering at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India. He received his PhD from IIT Roorkee and has published more than 100 research articles in scientific journals and conferences. He is a peer reviewer for numerous journals, acts as session chair in many international conferences, and conducts a number of training programs. He has organized five international conferences at NIT Jalandhar as organizing secretary and convener.
Dragan Pamucar, PhD, is an associate professor and earned his PhD from the University of Defence in Belgrade, Serbia. He has authored or co-authored over 50 papers in numerous scientific and technical journals, and, in 2017, he was awarded the top and outstanding reviewer award for his reviews in these journals.
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Dilbagh Panchal, PhD, is an assistant professor in the Department of Industrial and Production Engineering, Dr. B R Ambedkar National Institute of Technology Jalandhar, Punjab, India. He earned his PhD from the Indian Institute of Technology Roorkee, India. He has published 22 research papers in scientific journals, ten book chapters in various books, and he has edited two books. He is a reviewer for several scientific journals, and he is currently working on seven books, including books for Scrivener Publishing.
Mohit Tyagi, PhD, is an assistant professor in the Department of Industrial and Production Engineering at Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India. He earned his PhD from the Indian Institute of Technology, Roorkee, India, and he has over seven years of teaching and research experience. He has roughly 75 publications in scientific journals and has numerous conference proceedings and book chapters to his credit. He is a reviewer for many technical journals and has organized three international conferences.
Anish Sachdeva, PhD, is an associate professor in the Department of Industrial and Production Engineering at Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India. He received his PhD from IIT Roorkee and has published more than 100 research articles in scientific journals and conferences. He is a peer reviewer for numerous journals, acts as session chair in many international conferences, and conducts a number of training programs. He has organized five international conferences at NIT Jalandhar as organizing secretary and convener.
Dragan Pamucar, PhD, is an associate professor and earned his PhD from the University of Defence in Belgrade, Serbia. He has authored or co-authored over 50 papers in numerous scientific and technical journals, and, in 2017, he was awarded the top and outstanding reviewer award for his reviews in these journals.
Content
1 Speed Control of DC Motor at Variable Load Torque Using FLC 1 Kbrom Lbsu, Selomone Fantaye and Fisseha Teklay
1.1 Introduction 1
1.2 Background of Thesis Work 2
1.3 Statement of the Problem (Case Study) 2
1.4 Research Methods 3
1.5 Mathematical Model of DC Motor 5
1.6 Results and Discussion 7
1.7 Conclusion 9
References 10
2 Detailing and Analysis of Factors Governing Inventory in Dynamics of Food Supply Chain Performance System 11 Janpriy Sharma, Mohit Tyagi and Arvind Bhardwaj
2.1 Introduction 11
2.2 Literature Review 13
2.3 Methodology 14
2.4 Results and Discussions 25
2.5 Work Implications and Future Avenues 26
References 26
3 Risk Factor Appraisal in Cold Supply Chain Performance System through Delphi Based Hybrid MCDM Approach 31 Neeraj Kumar, Mohit Tyagi and Anish Sachdeva
3.1 Introduction and Background 31
3.2 Model Development (First Segment) 33
3.3 Research Methodology 34
3.4 Numerical Illustrations 38
3.5 Results and Discussion 41
3.6 Managerial Implication and Future Scope 43
References 43
4 Exploring Interaction Among Barriers of Circular Supply Chains: A Case of Indian Rubber Industry 45 Somesh Agarwal, Mohit Tyagi and R.K. Garg
4.1 Introduction 45
4.2 Literature Survey 46
4.3 Methodology 49
4.4 Results and Discussion 56
4.5 Conclusion and Future Scope 57
4.6 Limitation of Study and Future Scope 58
References 58
5 Power Spectral Density Analysis of HRV to Evaluate Changes in ANS During Graded Head-Up Tilt and Head-Reverse Tilt 61 Anjali Sharma and Dilbag Singh
5.1 Introduction 61
5.2 Materials and Methods 62
5.3 Results and Discussion 67
5.4 Conclusion 71
References 71
6 Mathematical Modeling for Catalytic Combustion of Volatile Organic Compound (VOC) Methane During Warm-Up Behaviour in Catalytic Converter 73 Umang Bedi and Sanchita Chauhan
6.1 Introduction 73
6.2 Rate Kinetics 74
6.3 Modeling 74
6.4 Methodology to Solve Dimensionless Equations 76
6.5 Result and Discussions 76
6.5 Conclusion 81
6.6 Acknowledgments 82
Nomenclature 82
References 83
7 Numerical Investigation of Two-Phase Flow in a Horizontal T Junction 85 Parth Patpatiya, Sreejita Samadder and Vanshika Kapoor
7.1 Introduction 85
7.2 Literature Review 86
7.3 Methodology 90
7.4 Results and Discussions 92
7.5 Conclusion 98
References 98
8 Studies on Design of Flexible Pavement Using Resilient Modulus: A Review 101 Ashish Pratap Singh, Mayank Pathak, Rajiv Kumar and Kanish Kapoor
8.1 Introduction 101
8.2 Resilient Modulus 103
8.3 Importance of Subgrade Resilient Modulus 103
8.4 Effect On Pavement Design 104
8.5 Seasonal Variations 106
8.6 Changes in Water Content Have an Effect on Resilient Modulus 106
8.7 Perspective on Resilient Modulus 107
8.8 Conclusion 107
References 108
9 Study on Design of Top Shackle used in Cage Suspension Gear in Mines - FEA Approach 111 Shivam Jaiswal
9.1 Introduction 111
9.2 Research Background 113
9.3 Research Methods 114
9.4 Finite Element Analysis 115
9.5 Analysis and Result 120
9.6 Conclusion 122
9.7 Acknowledgement 123
References 123
10 A Review on Current Trends in Offshore Wind Energy 125 Atul Gautam, Pramod Sharma, Vilas Warudkar and J.L. Bhagoria
10.1 Introduction 125
10.2 Modelling and Simulation 127
10.3 Dynamic Response and Dynamic Analysis 128
10.4 Damping and Fragility Estimations 129
10.5 Optimizing the New Offshore Wind Turbine Design 130
10.6 Reliability Studies of Offshore Wind Turbines 131
10.7 Cost Assessment 131
10.8 Methods of Installing Monopole Foundations Offshore 132
10.9 Climate Change Influence on Design of Offshore Wind Farm in Indian Offshore Wind Energy Sector 134
10.10 Conclusions 135
References 135
11 Assessment of Offshore Wind Energy for Site 137 Atul Gautam, Pramod Kumar Sharma, Vilas Warudkar and J L Bhagoria
11.1 Introduction 137
11.2 Literature Review 138
11.3 Offshore Tower Design Condition 139
11.4 Methodology 140
11.5 Paradeep Data Collection 142
11.6 Results 143
11.7 Discussion 145
11.8 Conclusion 145
References 145
12 Optimizing Volume of Helical Compression Spring by Genetic Algorithm and Comparing with Simulated Annealing 147 Kishor Kumar and Meenu
12.1 Introduction 147
12.2 Design of Springs 148
12.3 Optimization Techniques 151
12.4 Discussion of Results 155
12.5 Conclusions 159
References 159
13 Topological Design Optimisation of Dental Implant 161 Abner Ankit Lawrence, Nikhil Singh, Rahul Davis, Mohd. Sahil Ansari, Yash Vardhan Tewari and Vishal Francis
13.1 Introduction 161
13.2 Research Methods 163
13.3 Result Discussion 167
13.4 Conclusion 171
References 171
14 Response Surface Methodology Approach for Combustion Analysis of Compression Ignition Engine Fueled with Jatropha Biodiesel Produced by Using Heterogeneous Catalyst 173 Aparna Singh, Shailendra Sinha and Akhilesh Kumar Choudhary
14.1 Introduction 173
14.2 Materials and Methods 175
14.3 Results and Discussion 178
14.4 Optimization 181
14.5 Validation 182
14.6 Conclusion 183
References 183
15 Thermal Performance Evaluation of Solar Air Heater with Different Roughness Designs 185 Junaid Ahmad Bhat
Nomenclature 185
15.1 Introduction 185
15.2 Solar Air Heater 187
15.3 Experimentation 187
15.4 Instrumentation Used 189
15.5 Experimental Procedure 189
15.6 Results and Discussion 189
15.7 Conclusion and Scope for Future 192
15.8 Future Scope 193
Bibliography 193
16 Study of Physical Attributes of Indian Coconut Leaves for Efficient Midrib Separation 195 Abi Varghese, Joby G. David, Mebin Toms Mathew, Mijo P. Saji and Sambhu Nair V. S.
16.1 Introduction 195
16.2 Materials and Methods 196
16.3 Results and Discussion 198
16.4 Conclusion 201
References 201
Appendix 202
17 Manual Solar Tracking System with Two Degrees of Freedom 205 Surya Kumar, Ritesh Ranjan, Niraj Kumar Poddar, Bikash Kumar, Adarsh Kumar, Shweta Kumari, Nitish Kumar, Ajay Kumar and Suman Kumar
17.1 Introduction 205
17.2 Design Methodology 206
17.3 Working Prototype 210
17.4 Working Principle 212
17.5 Conclusions 214
17.6 Acknowledgement 214
References 214
18 Critical Review on Tribometers and Their Contact Mechanism 217 Sumit Singhal, Ritwik Agarwal, Rajan Kumar and R.K. Dwivedi
18.1 Introduction 217
18.2 Types of Wear 219
18.3 Ball-On-Disc Tribometer Contact Mechanism 220
18.4 Disc on Disc Tribometer 220
18.5 Cylinder on Block Tribometer 221
18.6 Four Ball Tester 222
18.7 Fretting Testing Machine 222
18.8 Conclusion 224
References 224
19 Investigation on Tribological Performance of Ferro-Magnetic Fluid as Lubricant 227 Ashwani Singh, Lalit Thakur and Jaideep Gupta
19.1 Introduction 227
19.2 Materials and Methods 229
19.3 Results and Discussion 234
19.4 Conclusion 235
References 236
20 Application of State Space Method on Beam to Predict its Response in Time and Frequency Domain 239 Nitin Gupta, Ashok Kumar Bagha and Shashi Bahl
20.1 Introduction 239
20.2 Formulation of Beam 240
20.3 State Space Formulation 243
20.4 Results and Discussion 245
Software and Comparing it with Analytical Solutions 248
20.5 Conclusions 250
References 250
21 Finite Element Model Updating of Five Degree of Freedom Spring Mass System using Direct Updating Method 253 Abhishek Sharma, Dinesh Kumar Shukla, Ashok Kumar Bagha and Shashi Bahl
21.1 Introduction 253
21.2 Analytical Study 255
21.3 Results and Discussion 257
21.4 Conclusions 262
References 263
22 Design and Analysis of Two Wheeler Suspension Helical Compression Spring 265 Pravin B. Khope, Sagar D. Shelare and Shubham S. Gunjal
22.1 Introduction 265
22.2 Design of Spring 267
22.3 Analysis of Existing Spring 270
22.4 Analysis of Spring I 273
22.5 Analysis of New Spring II 275
22.6 Result 277
22.7 Conclusion 277
References 277
23 Automated Belt Conveyor System for Bolt and Washer Assembly 279 Subhash N. Waghmare, Sagar D. Shelare, Nischal P. Mungle and Krunal P. Mudafale
23.1 Introduction 279
23.2 Research Methods 280
23.3 Materials and Methods 280
23.4 Result Discussion 290
23.5 Conclusion 293
References 294
24 Design and Development of Spherical Roller Bearings: A Review 297 Nilay Bhavsar and Gurmitsingh Bassan
24.1 Introduction 297
24.2 Literature Review 298
24.3 Literature Outcome 304
24.4 Conclusion 305
References 305
25 Topological Design Optimisation of Tissue Engineering Scaffolds 307 Abner Ankit Lawrence, Nikhil Singh, Mohd. Sahil Ansari, Yash Vardhan Tewari and Vishal Francis
25.1 Introduction 307
25.2 Research Methods 311
Scan 313
25.3 Result Discussion 317
25.4 Conclusion 319
References 319
26 Design of Different Controllers of Cruise Control System on Inclined Plane 321 Saty Prakash Yadav and Amit Kumar Singh
26.1 Introduction 321
26.2 Modeling of Cruise Control 322
26.3 Controller Design 324
26.4 Simulation Results 327
26.5 Conclusion 331
References 332
27 Mechanical Properties for 3D Printing of Polymers through Fused Deposition Modelling 335 Brajesh Kumar, Ankush Raina, Ravi Pratap Singh and Mir Irfan Ul Haq
27.1 Introduction 335
27.2 3D Printing Techniques 336
27.3 Materials 339
27.4 Studies Related to Behaviour of 3D Printed FDM Parts 340
27.5 Conclusions and Future Scope 348
References 348
28 Novel Approach for Optimization of Machining Characteristics of Polymer Nanocomposites 353 Kuldeep Kumar, Jogendra Kumar, Vijay Kumar Singh, Rajesh Kumar Verma and Abhishek Singh
28.1 Introduction 353
28.2 Background and Problem Formulation 354
28.3 Experimentation 355
28.4 Parametric Optimization 357
28.5 Results and Discussion 358
28.6 Conclusion 362
References 363
29 Soft Computing Techniques and Aluminum Metal Matrix Composites 367 Nitish Singh Jammoria, Mir Irfan Ul Haq, Ravi Pratap Singh and Ankush Raina
29.1 Introduction 367
29.2 Soft Computing Techniques 368
29.3 Studies Related to Soft Computing Techniques 368
29.4 Conclusions 382
References 382
30 Sustainable Manufacturing Related Aspects in Turning: A Study on Tool Wear 391 Akshay Kumar Vadaliya, Anil B. Ghubade, Parveen Sharma and Anil Kumar
30.1 Introduction 391
30.2 Literature Survey 392
30.3 Experimental Procedure 393
30.4 Result and Discussion 398
30.5 Conclusion 399
References 400
31 Effect of Different Process Parameters and Manufacturing Design of Heat Sink: A Review 403 Anil Kumar Rao and Shamsul Haq
31.1 Introduction 403
31.2 Heat Sink Construction 404
31.3 Thermal Resistance 404
31.4 Materials 405
31.5 Previous Research Work 406
31.6 Conclusion 411
References 411
32 Effect of Crumb Rubber on Concrete by Partial Replacement of Fine Aggregates 415 Mayank, Ashish Pratap Singh, Vaibhav Chaturvedi, Ravi Pratap Singh, Parampreet Kaur, Shivangi and Amit Arora
32.1 Introduction 415
32.2 Materials Used 416
32.3 Results and Discussions 416
32.4 Conclusions 419
References 420
33 An Analytical Model for Estimation of Build Time in Fused Deposition Modelling 423 Faladrum Sharma and Uday Shanker Dixit
33.1 Introduction 423
33.2 A Deterministic Model for Time Estimation 426
33.3 Determination of Lower and Upper Limits of Time Estimates 431
33.4 Validation 432
33.5 Conclusion 434
References 436
34 Thermomechanical Analysis of Pulsed Laser Welded Thin Aluminium Alloy Sheets 439 Tapas Bajpai, Pankaj Kumar Gupta and Anup Malik
34.1 Introduction 439
34.2 Finite Element Modelling 440
34.3 Results and Discussion 444
References 446
35 CFD Analysis of Car Parking Area to Study Carbon Monoxide Levels 447 Rahul Gupta and Rajesh Kumar
35.1 Introduction 448
35.2 Computational Fluid Dynamics Analysis 449
35.3 Governing Equations 449
35.4 Turbulence Model 451
35.5 Computational Domain and Boundary Conditions 452
35.6 Numerical Method 454
35.7 Results and Discussion 454
35.8 Conclusions 460
References 460
36 Performance Analysis of Semi-Transparent Photovoltaic Thermal Module with Single and Double Pass Configuration 463 C.S. Rajoria, Pankaj Gupta, Dharmendra Singh and Amit Sharma
36.1 Introduction 463
36.2 System Description 464
36.3 Energy Analysis of DPSPVT 465
36.4 Economic Analysis 466
36.5 Results and Discussion 468
36.6 Conclusion 471
References 471
37 Mechanical and Corrosion Behavior of Al 5083 Alloy Processed by Multi Directional Forging at Cryogenic Temperature 473 D. Singh, C. S. Rajoria, J. P. Bhamu, S. Raykar, P. K. Gupta and S. K. Rajput
37.1 Introduction 473
37.2 Experimental Details 474
37.3 Result Discussion 476
37.4 Conclusion 482
References 482
38 Critical Review of Cold Spraying Coating Techniques 485 Sagar D. Shelare, Trupti S. Gajbhiye, Dipak M. Hajare and Subhash N. Waghmare
38.1 Introduction 485
38.2 Principle of Cold Spraying 487
38.3 Contact Phenomenon and Bonding Mechanism of Cold Spraying Process 488
38.4 Coatings by Cold Spray 489
38.5 Cold Spraying Coatings Applications 491
38.6 Advantages and Potential Challenges of Cold Splash upon Another Thermal Spray Processes 493
38.7 Conclusion 494
References 495
39 Experimental Study of Influence of Drilling Parameters on Delamination in Drilling Aircraft CFRP Composites Using DOE (Taguchi Method) 499 Mayuresh Kashikar, S.M. Patil and Sumeet Kalkar
39.1 Introduction 499
39.2 Materials and Methods 501
39.3 Results and Discussions 504
References 517
40 Programming of 6 Axis Articulated Robot for Industrial Applications 519 Huzefa Mashhood and Mohammed Ali
40.1 Introduction 519
40.2 Research Background 520
40.3 Specification Details of Robot 521
40.4 Experimental Work 524
40.5 Programming of ARISTO Robot 525
40.6 Development of Arena Model For Layout 529
40.7 Discussion on Simulation Results 531
40.8 Conclusion 531
References 532
41 Process Optimization of EDM Parameters Using TAGUCHI while Machining Aluminium Metal Matrix Composite 533 Divya Chandra, Nathi Ram Chauhan and Rajesha S.
41.1 Introduction 533
41.2 Material Selection 535
41.3 Machinability Analysis on MMCs using Electric Discharge Machining 535
41.4 Analysis of Process Parameters 537
41.5 Results and Discussion 537
41.6 Conclusion 542
References 542
42 Study of Thermal Conductivity of NiCrFeSi Based Ceramic Composite Coating 545 Rahul Yadav, Rahul Kumar Sah, Pulkit Mann, Deepak Kumar and Pushpendra Singh
42.1 Introduction 545
42.2 Research Background 546
42.3 Experimental Procedure 547
42.4 Calculations 550
42.5 Discussion 551
42.6 Result 551
References 551
About the Editors 555
Index 557
1
Speed Control of DC Motor at Variable Load Torque Using FLC
Kbrom Lbsu*, Selomone Fantaye and Fisseha Teklay
Mekell University, Ethiopia
Abstract
A DC motor is an electro-mechanical device which is used to drive different loads in many application areas such as industrial and home appliances. During operation, one of the basic parameters to be controlled is the speed of the motor, which is affected by the internal parameter of the motor and external load that is connected to it. Separately excited DC motors have been widely used in high performance applications and when a motor is desired to operate at constant speed, its speed varies due to variation of load torque. The objective of this thesis work is to control the speed of separately excited DC motors using a fuzzy logic controller considering different load torques. In order to control the speed of the DC motor we used a fuzzy logic controller in a MATLAB environment by varying load torque. First, an open loop system was designed and measured the speed, transient, and steady state error. Secondly, a PID controller was designed to control the speed of the motor by tuning (KP, KI, and KD) gains of the PID controller and measuring the speed, transient, and steady state error. On the other hand, a fuzzy logic controller was designed to control the speed of the motor by intelligent tuning, taking appropriate expert rules and comparing the result between a PID and fuzzy logic controller in the simulation result.
Finally, a fuzzy logic controller is a better controller than a PID controller by zero overshoot, reduction of 28.1% of settling, 27.87% of rise time, and 93.33% of steady state error. In addition to this, by solving nonlinear characteristics of the motor, it increases overall performance of the system.
Keywords: DC motor, PID controller, fuzzy controller
1.1 Introduction
The DC motor is an attractive piece of equipment in many industrial applications requiring variable speed and load characteristics for its ease of controllability. The speed control of a DC motor is very crucial in application where precision and protection are of the essence. The purpose of a motor speed controller is to take error correcting signals representing the required speed and to drive a motor at a fixed speed. DC motors have good speed control despondence and are widely used in speed control systems which need high control requirements, such as rolling mills, double-hulled tankers, high precision digital tools, etc. The speed of a DC motor can be varied by controlling the field flux, armature resistance, or terminal voltage that is applied to the armature circuit. Separately excited DC motors are mainly used as actuators in industrial applications. These motors have the advantage of having low friction, small size, high speed, low construction cost, and high torque.
1.2 Background of Thesis Work
DC motors used in many applications, such as still rolling mills, electric trains, electric vehicles, electric cranes, and robotic manipulators, require speed controllers to perform their tasks. The speed controller of DC motors was first carried out by means of voltage control in 1981 by Ward Leonard [2]. DC motors use feedback controllers to control the speed, position, or both. Today, the most famous and frequently used type of controller in the industry is a PID controller, but PID controllers do not offer satisfactory results when an adaptive algorithm is required [6]. Fuzzy logic control (FLC) is one of the most successful applications of fuzzy set theory, introduced by L.A Zadeh in 1973 and applied (Mamdani 1974) in an attempt to control systems that are structurally difficult to model. Since then, FLC has been an extremely active and fruitful research area with many industrial applications reported [3]. In the last three decades, FLC has evolved as an alternative complementary to the conventional control strategies in various engineering areas. Fuzzy control theory usually provides non-linear controllers that are capable of performing different complex non-linear control actions, even for uncertain nonlinear systems.
1.3 Statement of the Problem (Case Study)
Since DC motors have wide applications, the speed can be varied due to different condition. When a motor is desired to operate in a constant speed, its speed may be varied due to different loads; the speed of motor is decreased when the load is increased and the speed of the motor is increased when the load is decreased, so consequently the motor does not accurately work at the desired time. Machines are easily damaged without implementation of control methodology in the system and the conventional (PI, PD, PID) technique is widely used in DC motor speed and position control. It is not suitable for high performance cases because of the low robustness of PID controllers. Not only that, but the major problems in applying a conventional control system in a speed controller are the effects of nonlinear characteristics of a DC motor, such as saturations and fictions, that could degrade the performance of conventional controllers. This thesis work proposes a new ability of fuzzy logic control, whose approach offers a simpler, quicker, and more reliable solution that has clear advantages over conventional techniques and a control system that could give a faster response in order to maintain the speed of the DC motor at the desired value with minimum overshoot, minimum steady state error, minimum settling time, and fast rising time, all of which are very important and crucial in industrial application.
1.4 Research Methods
1.4.1 Fuzzy Logic Controller Theory
The fuzzy logic idea is similar to the human being's feeling and inference process, unlike the classical control strategy as shown in Figure 1.1.
Figure 1.1 Structure of fuzzy logic controller.
The principal elements of a fuzzy logic controller are:
- A. Fuzzification
- B. Rule Base and Inference Engine
- C. Defuzzification
A. Fuzzification
This process converts the crisp input into the fuzzy linguistic values. Generally, fuzzy logic uses linguistic variables instead of any precise or numerical variables.
B. Rule Base and Inference Engine
A collection of rules is called a rule base. The rules are in an if/then format; formally, the "if" side is called the condition and the "then" side is called the conclusion.
- ? Fuzzy Inference Model
- (A). Mamdani Model: Mamdani-type inference, as defined for the toolbox, expects the output membership functions to be fuzzy sets. After the aggregation process, there is a fuzzy set for each output variable that needs defuzzification [4].
- (B). Segeno Model: The Segeno, or Takagi-Kang, Method of fuzzy inference is mostly similar to the Mamdani model, but the difference is Segeno output membership functions are either linear or constant and the rule base of the Segeno is: If x is A and y is B, then z is F(x, y). This model is mainly used if there is no expert knowledge about the system [5].
C. Defuzzification
The reverse of fuzzification is called defuzzification. It is the transformation of a fuzzy quantity into a precise quantity, just like fuzzification is the conversion of a precise quantity to a fuzzy quantity. The use of a fuzzy logic controller (FLC) produces the required output in a linguistic variable (fuzzy number). As per real world requirements, the linguistic variables should be transformed to a crisp output. We have been used the center of the area for the defuzzification process in this paper [1].
There are five basic defuzzification strategies and they are defined as follows:
- Centroid of Area (COA): It is one of the most popular techniques used for defuzzification, as it is reminiscent of the calculation of expected values of probability distributions. It can be defined as follows: (1.1)
where µA (Z) is the aggregated output MF.
- Bisector of Area (BOA):
It satisfies the equation: (1.2)where a = min {z/z ? z} and ß = max {z/z ? z}, that is the vertical line, and z = zBoA partitions the region between z = a, z = ß, y = 0, and y = µA into two regions with the same area.
- Mean of Maximum (MOM):
zmom is the average of the maximizing z at which the MF reaches a maximum µ*. It can be represented as follows: (1.3)where z' = {z | µA (z) = µ*}.
- Smallest of Minimum (SOM):
zSOM is the minimum of the maximizing z (in terms of magnitude). - Largest of Maximum (LOM):
zLOM is the maximum of the maximizing z (in terms of magnitude).
Fuzzy Input:
- i) Error of speed (5 membership)
- ii) Change of speed error (5 membership)
Fuzzy Output:
- i) Control output (5 memberships)
Fuzzy Inference System: Mamdani
Defuzzification Method: Centroid
Rules Base: 25 rules
Figure 1.2 Block diagram of DC motor with fuzzy logic controller.
1.5 Mathematical Model of DC Motor
Figure 1.3 Model of DC motor.
According to the Kirchhoff's voltage Law, the electrical equation of the DC motor is
(1.4)where ia(t) is the armature current, Vb(t) is the...
