Crane Operator Performance Comparing PD-Feedback Control and Input Shaping Ajeya Karajgikar (with Dr. Joshua Vaughan and Dr. William Singhose) 10 th November,

Crane Operator Performance Comparing PD-Feedback Control and Input Shaping

Ajeya Karajgikar

(with Dr. Joshua Vaughan and Dr. William Singhose)

10th November, 2011

Weekly Group Meeting Presentation

Sensing Crane Payloads Can be Difficult

• Sensing hook and payload is not trivial even in ideal conditions

• Distinguishing between the hook and payload using machine vision can be difficult

Conflict Between Feedback and Human Operators

• Conceptual Block Diagram of the PD Crane Controller

Using Input Shaping to Reduce Unwanted Payload Oscillations

• Payload oscillation after a point-to-point move makes it difficult for accurate position while decreasing safety

Using Input Shaping to Reduce Unwanted Payload Oscillations

• Payload oscillation after a point-to-point move makes it difficult for accurate position while decreasing safety

• Input shaping can be used to solve this problem

Conflict Between Feedback and Human Operators

• Conceptual Block Diagram of Input-Shaping Controller

• Conceptual Block Diagram of the PD Crane Controller

10-ton Industrial Bridge Crane

Single Pendulum and Double Pendulum Effects

• Single Pendulum Case

• Double Pendulum Case




Point-to-point movements (without shaping)

• Hook was moved from one point to another point over a distance of 3m manually

Point-to-point movements (PD-Feedback Control)


Point-to-point movements (with shaping)


Hook Angle Response Point-to-point movements

• Hook angle response when hook was moved from one point to another point over a distance of 3m manually

10-ton Industrial Bridge Crane and Obstacle Course

Example Operator Performance - Manual Control

• Unshaped response of hook position when an operator maneuvers through the obstacle course (t = 165s)

Example Operator Performance – PD-Feedback


Example Operator Performance – Input Shaped


Completion Times by each Operator

• Completion times of twelve novice crane operators

Average Completion Times• Completion time with PD-control was 74% less than

manual control (37s vs. 140s)• Input shaping further reduced the average completion

time to 32s, representing a 14% reduction from PD control and a 77% reduction from manual control

Distance Traveled – Unshaped

• Travel distance of trolley and hook by twelve novice crane operators

Distance Traveled – PD-Feedback


Distance Traveled – Shaped


Total Distance Traveled by Trolley• The shorter total travel distance afforded by

input shaping provides evidence that is more energy efficient than either manual control or PD control (9.52m vs 7.84m vs 7.51m)

Total Distance Traveled by Hook• The shorter total travel distance traversed by

the hook shows how well the hook can track the desired path (60.33m vs 10.02m vs 7.79m)

Collisions by each Operator

• Collisions of twelve novice crane operators (Unshaped = 13; Feedback = 0; Shaped = 0)




Point-to-point movements

• Point-to-point moves with controllers designed for Double Mode

• Point-to-point moves with controllers designed for Single Mode

• Point-to-point moves with controllers designed for Double Mode with changes in payload configuration





Point-to-point movements (without shaping)




(Double Pendulum gains)



(Two Mode ZV Shaper)








• Point-to-point moves with controllers designed for Double Mode• Point-to-point moves with controllers designed for

Single Mode The masses are kept the same but the gain and

shaper parameters are changed• Point-to-point moves with controllers designed for

Double Mode with changes in payload configuration



(Single Pendulum gains)



(One Mode ZV Shaper)









• Point-to-point moves with controllers designed for Double Mode• Point-to-point moves with controllers designed for Single

Mode• Point-to-point moves with controllers designed for

Double Mode with changes in payload configuration Different masses were attached, but the gain and

shaper parameters were left unchanged mp was changed from 50 lbs to:

Case (1) 25 lbs and Case (2) 75 lbs Testing the robustness of the controller



(Double Pendulum gains, 25 lbs)



(Two Mode ZV Shaper, 25 lbs)



(Double Pendulum gains, 75 lbs)



(Two Mode ZV Shaper, 75 lbs)

Example Operator Performance - Manual Control


Example Operator Performance – PD-Feedback


Example Operator Performance – Input Shaped


Completion Times by each Operator

• Completion times of ten novice crane operators

Average Completion Times• Completion time with PD-control was 66% less than

manual control (55s vs. 161s)• Input shaping further reduced the average completion

time to 38s, representing a 31% reduction from PD control and a 76% reduction from manual control

Distance Traveled – Unshaped

• Travel distance of trolley and hook by ten novice crane operators

Distance Traveled – PD-Feedback


Distance Traveled – Shaped


Total Distance Traveled by Trolley• The shorter total travel distance afforded by

input shaping provides evidence that is more energy efficient than either manual control or PD control (9.52m vs 9.07m vs 7.88m)

Total Distance Traveled by Hook• The shorter total travel distance traversed by

the hook shows how well the hook can track the desired path (44.72m vs 14.17m vs 9.77m)

Collisions by each Operator

• Collisions of ten novice crane operators (Unshaped = 18; Feedback = 2; Shaped = 0)

Summary

• Both PD-Feedback control and Input Shaping significantly reduce oscillation

• Using PD-Feedback control presents difficulty in sensing payload and human operator compatibility problems

• Input Shaping produced the lowest average task completion times and shortest average trolley travel distance

• Input Shaping was the safest in terms of obstacle avoidance

Questions, comments, concerns?

Crane Operator Performance Comparing PD-Feedback Control and Input Shaping Ajeya Karajgikar (with Dr. Joshua Vaughan and Dr. William Singhose) 10 th November,

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