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کنترل فعال ارتعاشات ربات ها در عملیات ماشینکاری با استفاده از عملگر پیزوالکترونیک
محمدی دانیالی، محسن Mohammadi Daniali, Mohsen
Cataloging brief
کنترل فعال ارتعاشات ربات ها در عملیات ماشینکاری با استفاده از عملگر پیزوالکترونیک
پدیدآور اصلی :
محمدی دانیالی، محسن Mohammadi Daniali, Mohsen
ناشر :
صنعتی شریف
سال انتشار :
1387
موضوع ها :
ربات شناسی Robotics عملگر پیزوالکتریک Piezoelectric Actuator کنترل کننده عصبی - فازی...
شماره راهنما :
58-39285
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TITLE OF THE THESIS.pdf
(1)
Master Thesis
(14)
Chapter 1: Introduction
(14)
1.1 problem statement
(14)
1.2 literature review
(15)
1.2.1 Robotic automation of finishing operations
(15)
a. robotic deburring researches
(15)
Figure 1.1 Cutting surface area in edge deburring process [5]
(16)
b. other researches
(20)
1.2.2 Vibration control of robot manipulators with flexible joints
(21)
a. free motion
(21)
b. constrained motion
(23)
1.2.3 Active vibration control of machine tools
(28)
Figure 1.2 Section view of turning system [33]
(30)
Figure 1.3 Schematic design of the chuck-pallet system with active vibration control elements [35]
(32)
1.3 project approach
(32)
Figure 1.4 Proposed system configuration for a two-link manipulator in deburring process
(33)
Figure 1.5 Schematic diagram of vibration control of robotic deburring
(34)
Chapter 2: Robot Dynamics and Control
(35)
2.1 introduction
(35)
Figure 2.1 Schematic diagram of a two-link planar manipulator [22]
(35)
2.2 robot modeling
(36)
2.2.1 dynamic model of two-link manipulator
(36)
(2-1)
(36)
Figure 2.2 Coordinates of the two-link manipulator
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, (2-2)
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(2-3)
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(2-4)
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(2-5)
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(2-6)
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(2-7)
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(2-8)
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(2-9)
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(2-10)
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2.2.2 modeling of mechanical and electrical parts
(38)
Figure 2.4 Modeling of the mechanical part as a 3-mass system
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(2-11)
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(2-12)
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(2-13)
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(2-14)
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(2-15)
(39)
(2-16)
(40)
2.3 robot controller
(41)
(2-17)
(41)
(2-19)
(41)
(2-21)
(42)
2.4 simulation
(42)
Table 2.1 Simulation conditions for two-link robot manipulator with flexible joints
(43)
Figure 2.6 SIMULINK . diagram of the simulation
(44)
Figure 2.7 DC motor . and gear subsystem
(45)
2.5 simulation results
(46)
Figure 2.8 Robot end-effector position in x direction versus time
(46)
Figure 2.13 Random force exerted at the tip of the robot in y direction
(49)
Chapter 3: Deburring process
(51)
3.1 introduction
(51)
3.2 dynamic deburring model
(52)
3.2.1 Cutting forces
(52)
(3-1)
(52)
(3-3)
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(3-5)
(53)
3.2.2 Dynamic-regenerative chip thickness
(54)
(3-7)
(54)
Figure 3.3 Dynamic regenerative chip thickness
(54)
(3-8)
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(3-9)
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(3-10)
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(3-11)
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(3-12)
(55)
3.2.3 Axial depth of cut
(56)
(3-13)
(56)
(3-14)
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(3-15)
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(3-16)
(56)
(3-19)
(57)
3.3 simulation
(57)
(3-20)
(58)
Figure 3.4 Block diagram of regenerative vibration in deburring process
(58)
Figure 3.5 Deburring model with two degree of freedom
(59)
Table 3.1 Simulation conditions for deburring with flexible structure
(60)
Figure 3.8 Burr height as a random signal
(62)
Chapter 4: Piezoelectric actuator
(63)
4.1 introduction
(63)
4.2 physical background
(63)
Figure 4.1 Schematic representation of the different relations in a piezoelectric actuator [41]
(64)
Figure 4.2 Illustration of a piezoelectric stack actuator
(65)
4.3 piezoelectric actuator modeling
(66)
(4-1)
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(4-2)
(66)
4.3.1 Electromechanical model
(67)
Figure 4.3 Electromechanical model [41]
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(4-3)
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(4-6)
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(4-8)
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(4-10)
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(4-12)
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4.3.2 Hysteric model
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(4-14)
(70)
Figure 4.4 Realistic hysteresis loop [41]
(70)
(4-15)
(71)
(4-17)
(71)
(4-19)
(71)
4.3.3 Mechanical model
(71)
Figure 4.5 Piezoelectric actuator in undeformed and deformed state
(72)
(4-20)
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(4-21)
(73)
l= 0 (4-23)
(73)
l= n (4-24)
(73)
Figure 4.6 Chain of mass-spring-damper systems as an mechanical model of piezoelectric actuator
(73)
4.3.4 Mechanical model of a piezo-actuated positioning mechanism
(74)
Figure 4.6 Total system of piezoactuator and mass-spring-damper system (stage)
(74)
(4-25)
(75)
(4-26)
(75)
(4-27)
(75)
(4-28)
(75)
Figure 4.9 Root Locus for increasing value of the stage mass ( 0 < ms < mp ) [41]
(77)
(4-29)
(78)
(4-30)
(79)
(4-32)
(79)
4.3.5 Charge steering configuration
(79)
Figure 4.10 Actuator hysteresis curve for voltage steering (control) [42]
(80)
Figure 4.11 Actuator hysteresis curve for charge steering (control) [42]
(80)
Figure 4.12 Basic configuration for charge control [41]
(81)
(4-33)
(81)
4.3.6 Total model for the case of charge control
(81)
(4-34)
(82)
(4-36)
(82)
(4-38)
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(4-39)
(82)
(4-41)
(82)
Chapter 5: Intelligent controller
(83)
5.1 introduction
(83)
5.2 active vibration control
(84)
5.2.1 Feedback control
(85)
Figure 5.1 The components of a feedback control system [45]
(86)
5.2.2 Feedforward control
(87)
Figure 5.2 The components of a feedforward control system [45]
(88)
Figure 5.3 Active control system with filtered-reference LMS algorithm based control
(90)
Figure 5.5 Block diagram of feedforward active vibration control structure
(91)
(5-1)
(92)
(5-3)
(92)
Figure 5.6 Neuro-modeling of the inverse plant Q0-1 [47]
(93)
Figure 5.7 Neuro-modeling of the plant Q1 [47]
(94)
Figure 5.8 Training the neuro-controller [47]
(94)
5.3 neuro-pid controller
(95)
(5-4)
(95)
Figure 5.9 Neuro-PID structure
(96)
(5-5)
(96)
(5-9)
(96)
(5-12)
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(5-14)
(97)
(5-15)
(97)
5.4 adaptive critic-based neurofuzzy controller
(97)
5.4.1 Neurofuzzy networks [55]
(100)
Rj ( jth rule ) : If ( x1 is Fj1 ) and ( x2 is Fj2 ) and … and ( xn is Fjn ) Then cj = gj ( X )
(100)
(5-16)
(101)
(5-17)
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(5-18)
(101)
(5-19)
(101)
Figure 5.9 A sample neurofuzzy structure equivalent with a MISO TSK fuzzy inference system [55]
(102)
Figure 5.10 Structure of adaptive critic-based neurofuzzy controller
(103)
5.4.2 Learning algorithm
(103)
(5-20)
(103)
(5-21)
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(5-22)
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(5-23)
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(5-24)
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(5-25)
(105)
(5-26)
(105)
(5-27)
(105)
(5-28)
(106)
5.5 controller design for active vibration suppression
(106)
(5-30)
(106)
Figure 5.12 The error derivative membership functions of the corresponding linguistic variables of the proposed neurofuzzy controller
(107)
Figure 5.14 The parameters of fuzzy inference system
(109)
Table 5.1 Fuzzy rules for critic
(110)
Chapter 6: Simulation results
(111)
Table 6.1 Parameter values for piezoelectric actuator
(116)
Table 6.2 Stage (mass, spring, and damper) parameters value
(116)
Figure 6.7 Block diagram of active vibration control using piezoelectric actuator
(117)
Figure 6.8 Overall position yo before and after applying neuro-PID controller
(118)
Figure 6.9 Overall position yo before and after applying adaptive critic-based neurofuzzy controller
(119)
Figure 6.10 Performance comparison of neuro-PID and ACNF controllers
(120)
References
(121)
paper 2
(127)
I. Introduction
(127)
II. modeling of a two-link manipulator with flexible joints
(128)
III. modeling of deburring process
(128)
IV. modeling of piezoelectric actuator
(129)
V. adaptive critic-based neurofuzzy structure
(130)
VI. simulation results
(130)
VII. conclusion
(131)
References
(131)
