haptic control of hydraulic machinery using proportional valves

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6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 VII HAPTIC CONTROL AND EVALUATION . . . . . . . . . . . . . . . . 143 7.1 Coordinated Haptic Control . . . . . . . . . . . . . . . . . . . . . . 144 7.2 Impedance Shaping . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 7.3 Human Factors Evaluation . . . . . . . . . . . . . . . . . . . . . . . 151 7.3.1 Controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 7.3.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 7.3.3 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . 154 7.3.4 Force on Environment . . . . . . . . . . . . . . . . . . . . . 154 7.3.5 Digging Productivity . . . . . . . . . . . . . . . . . . . . . . 159 7.3.6 Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 7.3.7 Subjective Comments . . . . . . . . . . . . . . . . . . . . . 165 7.3.8 Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 7.4 Virtual Fixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 7.5 Passive Energy Balance Monitoring . . . . . . . . . . . . . . . . . . 174 7.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 VIII CONTRIBUTIONS AND FUTURE WORK . . . . . . . . . . . . . . . 180 8.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 8.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 8.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 APPENDIX A SFUN BH C2J.C . . . . . . . . . . . . . . . . . . . . . . . 186 APPENDIX B LAGRANGIAN DYNAMICS . . . . . . . . . . . . . . . . . 195 APPENDIX C STATISTICS SUMMARY . . . . . . . . . . . . . . . . . . 203 APPENDIX D HUMAN TESTING PROCEDURE . . . . . . . . . . . . . 210 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 VITA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 viii
LIST OF TABLES 3.1 Denavit-Hartenberg parameters. . . . . . . . . . . . . . . . . . . . . . 24 4.1 Controller parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.1 MSE for each degree-of-freedom. . . . . . . . . . . . . . . . . . . . . . 121 5.2 Parameters from sequential LLS, concurrent LLS and CAD . . . . . . 122 7.1 HEnRE and V-HEnRE digging force paired t-test . . . . . . . . . . . 155 7.2 Digging force peaks paired t-test . . . . . . . . . . . . . . . . . . . . . 157 7.3 Average digging force paired t-test . . . . . . . . . . . . . . . . . . . 157 7.4 Largest force peakson object paired t-test . . . . . . . . . . . . . . . . 158 7.5 All force peakson object paired t-test . . . . . . . . . . . . . . . . . . 158 7.6 Digging productivity paired t-test . . . . . . . . . . . . . . . . . . . . 160 7.7 Average haptic force paired t-test . . . . . . . . . . . . . . . . . . . . 161 7.8 Number of hits paired t-test . . . . . . . . . . . . . . . . . . . . . . . 162 7.9 Success rate detecting the objects for different controllers. . . . . . . 163 7.10 Detection time from first nick paired t-test . . . . . . . . . . . . . . . 164 7.11 Detection time comparison paired t-test . . . . . . . . . . . . . . . . 164 C.12 Confidence interval data for digging force . . . . . . . . . . . . . . . . 204 C.13 Paired t-test data for digging force . . . . . . . . . . . . . . . . . . . 204 C.14 Confidence interval data for digging force peaks . . . . . . . . . . . . 205 C.15 Confidence interval data for average digging force . . . . . . . . . . . 205 C.16 Paired t-test data for digging force peaks . . . . . . . . . . . . . . . . 205 C.17 Paired t-test data for average digging force . . . . . . . . . . . . . . . 205 C.18 Confidence interval data for the largest force peaks . . . . . . . . . . 206 C.19 Confidence interval data for all force peaks on object . . . . . . . . . 206 C.20 Paired t-test data for the largest force peaks on object . . . . . . . . 206 C.21 Paired t-test data for all force peaks on object . . . . . . . . . . . . . 206 C.22 Confidence interval data for digging productivity . . . . . . . . . . . . 207 C.23 Paired t-test data for digging productivity . . . . . . . . . . . . . . . 207 ix
Page 1 and 2: HAPTIC CONTROL OF HYDRAULIC MACHINE
Page 3 and 4: To those who have encouraged me, be
Page 5 and 6: work hard on my weaknesses. A speci
Page 7: IV HYDRAULIC CONTROL . . . . . . .
Page 11 and 12: LIST OF FIGURES 2.1 4-channel archi
Page 13 and 14: 5.6 Force sensor picture . . . . .
Page 15 and 16: CHAPTER I INTRODUCTION The word hap
Page 17 and 18: dead-band. Servo valves also have t
Page 19 and 20: that worked well for free motion di
Page 21 and 22: many haptic researchers strive to a
Page 23 and 24: guarantee the stability of coupled
Page 25 and 26: of the teleoperator because it redu
Page 27 and 28: indicate improved accuracy, better
Page 29 and 30: so that h 12 h 21 = −1. With this
Page 31 and 32: can track a desired trajectory. The
Page 33 and 34: Deere tractor with a Model 47 backh
Page 35 and 36: CHAPTER III KINEMATICS Today almost
Page 37 and 38: • y ci - ith cylinder length •
Page 39 and 40: x = rcos(θ) y = rsin(θ) (3.2) z =
Page 41 and 42: 100 θ 2 +θ 3 +θ 4 z(cm) 75 50 25
Page 43 and 44: ⎡ ⎤ P 43 × ê z4 = ⎢ ⎣ −
Page 45 and 46: distal case is ⎡ d cyl = 1 d d
Page 47 and 48: 100 75 z(cm) 50 25 0 O 2 a 3 θ O 1
Page 49 and 50: 250 200 Edge of Regions Manipulator
Page 51 and 52: ⎡ ∇ Ξ L T = ⎢ ⎣ ⎤ W r (r
Page 53 and 54: large changes in r and z to allow
Page 55 and 56: desired position (master position)
Page 57 and 58: esponse when the constraint is enfo
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θ K0J = θ MJ0 + π/2 + θ 1 −
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3.3.3 Stick Cylinder D y 3 C θ 2
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R FHy = R FH sin(α + θ EFH ) (3.9
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constraints. Two methods for dealin
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flow control strategies are demonst
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pressure regulating configurations
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4.2.1 Proportional Directional Cont
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P p P s Figure 4.4: Schematic of Sa
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120 Sample mean 99% C.I. 100 80 Cro
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Pressure(psi) 1500 1000 500 P s LS
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4.3 Pump Pressure Control From an e
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F cyl = ∂θ ∂x cyl τ = A c P c
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M eq¨˜x cyl = ∂θ ∂x cyl (¯x
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This means that if the pressure dri
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s x d + Σ - e K d s + K p + + Σ v
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eing controlled using a load-sensin
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Figure 4.20 shows the same response
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Y cyl (cm) Pressure (MPa) Flow (L/m
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4.3.4 Max Pressure Filter How the s
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15 Pressure(MPa) 10 5 P sd P sdf P
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100 80 Actual Desired Start End z
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4.4 Actuator Flow Control The previ
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20 15 Data: wo/ Pcomp Trendline: wo
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eturn P s return main spool P c , Q
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v d + y + e d Σ G cp + Σ v dc G c
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v dc Q req Q cmd + γ Σ − Vel2fl
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control block as separated from and
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4.4.3 Dead-band Transition The prop
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the PI-lead and one with only the p
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1 Elbow Trajectory ∆φ( o ) 0 −
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4.5 Summary This chapter addresses
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CHAPTER V BUCKET FORCE Using pressu
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load pins on the cylinder bases. Co
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5.1.2 LS-Estimation 100 z(cm) 75 50
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Second, velocity needs to be separa
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s 23 = sin(θ 23 ) (5.21) ⎡ ⎤
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⎡ W24 T = ⎢ ⎣ ⎤ gc 24 gc 24
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6 Sequential LLS Bucket−Force(kN)
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Table 5.1: MSE for each degree-of-f
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5.2 Load Cell Measurement D E y 4 H
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Just like the hydraulic force inclu
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⎡ ⎤ Φ = ⎢ ⎣ J 4 l 4 m 4 c
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10 5 F r (kN) 0 −5 Sen Est −10
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CHAPTER VI VIRTUAL BACKHOE In order
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y assuming that valve flow is only
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⎡ ⎤ ⎡ ⎤ ⎡ ⎤ ⎢ ⎣ f b
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⎧ ⎪⎨ λ = ⎪⎩ 0 t < t c &
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100 80 V−HEnRE HEnRE Desired Star
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1 ∆φ( o ) 0 −1 0 1 2 3 4 5 6 7
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CHAPTER VII HAPTIC CONTROL AND EVAL
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velocity, v h are mapped into the b
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Even though it is not used in the h
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0.5 v dc "(m/s) 0 −0.5 0.5 −5 0
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Substituting for the F stall from E
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fact that there was no limit on buc
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10 8 Force (kN) 6 4 2 0 HEnRE − f
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10 8 F dig−peak F dig−ave Force
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7.3.5 Digging Productivity The same
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2 1.5 Force(N) 1 0.5 0 half full of
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Table 7.9: Success rate detecting t
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7.3.7 Subjective Comments Comments
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• “Bucket filled with dirt auto
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7.3.8 Learning As previously mentio
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7.4 Virtual Fixtures Another way to
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90 80 Workspace Limits Path−backh
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The physical power entering the sys
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Human Operator v h f h Master Inter
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The controllers are evaluated using
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scheme called Impedance Shaping is
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elated to bucket torque. In additio
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9. Install a bigger constant displa
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***********************************
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ssSetOutputPortSampleTime(S, 0, Ts)
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f3 = U[10]; f4 = U[11]; /**********
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Y[6] = w3; Y[7] = w4; Y[8] = T1; Y[
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APPENDIX B LAGRANGIAN DYNAMICS The
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The gravity term, G(Θ) originates
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⎡ ω 4|1 = ⎢ ⎣ ⎤ −s 24 ˙
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V (Θ, ˙Θ) = ∂2 KE ∂KE ∂Θ
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APPENDIX C STATISTICS SUMMARY C.1 M
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Table C.14: Confidence interval dat
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Page 223 and 224:
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11. The test was complete with an o
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REFERENCES [1] Adams, R. J. and Han
Page 229 and 230:
[26] Fite, K. B., Goldfarb, M., and
Page 231 and 232:
[53] Hirata, T., Yamagata, E., Wata
Page 233 and 234:
[78] Lamgreth, R., “Smarter shove
Page 235 and 236:
[104] Nguyen, Q., Ha, Q. P., Rye, D
Page 237 and 238:
[129] Tafazoli, S., Peussa, P., Law
Page 239 and 240:
[153] Young, G. N. and Alft, K. L.,
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