Abstract 4-5
Abstract 5
1 Introduction 9- 14
1. 1 Development and present situation of magnetic levitation technology 9
1.2 Development background and significance of maglev train 9- 1 1
1.3 development of maglev trains at home and abroad 1 1
1.4 control of maglev train 1 1- 12
1.4. 1 control characteristics 1 1- 12
1.4.2 quality control requirements
1.5 paper 12- 14 main work
Dynamic model and modal analysis of 2 maglev train 14-23
2. 1 force-air gap distance relation of magnetic suspension system 14- 16
2.2 dynamic model of single electromagnet 16- 19
2.2. 1 system working principle 16- 19
2.3 local linearization of single iron dynamic model 19-2 1
2.4 system model analysis 2 1-23
3 magnetic suspension controller design 23-40
3. 1 design of double-loop control system 23-28
3. 1. 1 Design of current loop 23-25
3. 1.2 Design of Double-loop Controller 25-28
3.2 Design of linear gain state feedback controller 28-33
3.2. 1 System Equation 29
3.2.2 Closed-loop pole configuration 29-3 1
3.2.3 determination of state feedback matrix k 3 1-32
3.2.4 Digital Simulation of Linear Gain State Feedback Controller
3.3 PI state feedback controller design 33-37
3.4 Simulation Comparison of Control Schemes 37-40
3.4. 1 Performance of controller in suppressing external interference 37-40
4 Principle and composition of magnetic suspension system 40-49
4. 1 system working principle 40-4 1
4.2 Composition of Magnetic Levitation System 4 1-49
4.2. 1 eddy current sensor 4 1-43
4.2.2 Electromagnetic current drive unit 43-45
4.2.3 IGBT drive circuit 45-48
Linear motors 48-49
5 controller implementation and experimental results 49-59
5. Hardware circuit implementation of1PID controller 49-54
PID controller 49-5 1
5. 1.2 driving circuit 5 1
5. 1.3 peripheral circuit 5 1-54
5.2 Experimental Results and Analysis 54-55
5.3 Cross-coupling problem 55-59
Design of fuzzy controller for 59-67 maglev train
6. Design of1fuzzy controller 59-67
6. 1. 1 Determination of language values and membership functions of fuzzy language variables 59-6 1
6. 1.2 defines the scale factor of 6 1.
6. 1.3 Consider choosing the fuzzy language variable value 6 1-62.
6. 1.4 Fuzzification and deblurring 62-63
6. 1.5 fuzzy control decision 63-65
6. 1.6 Simulation study 65-66
6. 1.7 Summary
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