7/22/2019 Fuzzytech Crane Simulation
1/27
Case Study
Container Crane Control
7/22/2019 Fuzzytech Crane Simulation
2/27
Objectives of Ports
For delivery of goods through containerstransported by cargo ships.
Example is PTP in Johore, Wesport in
Klang and of course Singapore.
7/22/2019 Fuzzytech Crane Simulation
3/27
Crane Productivity
Crane productivity ismeasured by how fast thePort Authority can movethe cranes.
Singapore = 25moves/hour
Jakarta = 17 moves/hour
Malaysia Westport=22moves/hour
7/22/2019 Fuzzytech Crane Simulation
4/27
Crane Productivity in Westport,
Port Klang
7/22/2019 Fuzzytech Crane Simulation
5/27
Container Crane Simulator
7/22/2019 Fuzzytech Crane Simulation
6/27
Container Crane Control
Loading and unloading ofcontainers are done inharbors in every countryaround the world.
For transportation ofmanufactured goods,food, etc.
Container cranes areused for such purpose.
7/22/2019 Fuzzytech Crane Simulation
7/27
Operations and Problems
When a container is picked up and the cranehead starts to move, the container begins tosway.
Swaying of the container is not a problem duringtransportation but a swaying container cannot bereleased.
7/22/2019 Fuzzytech Crane Simulation
8/27
Container Crane Control
Two ways to solve this problem:
1.To position the crane head exactly over the targetposition, and then just wait until the sway dampens to
an acceptable level.
2.To pick up the container and just move slowly that nosway ever occurs.
Both ways would be alright on a non-windy day but ittakes too much time.
An alternative is to build container cranes whereadditional cables fix the position of the containerduring operation- but this would be too expensive.
7/22/2019 Fuzzytech Crane Simulation
9/27
For these reasons, most container cranesuse continuous speed control of the cranemotor- a human operator then control thespeed of the motor.
The operator has to simultaneouslycompensate for the sway and make surethe target position is reached in time.
This is not an easy and would need veryskilled operators.
7/22/2019 Fuzzytech Crane Simulation
10/27
Several Control Modes Many engineers have tried to automate this
control task of controlling the crane by using: Conventional PID Control
Model-based control
Fuzzy logic control
Problems with PID This is a nonlinear problem.
Minimizing the swaying of the container is important whenthe container is closed to the target where PID is insufficientdue to high nonlinearity.
Problems with Model-based control Usually math-models tend to be an assumption (reduced-
order model) and the crane motor behavior is far less linearthan assumed in the model.
The crane head only moves with friction. Disturbances such as wind cannot be modelled easily.
7/22/2019 Fuzzytech Crane Simulation
11/27
A Linguistic Control Strategy
A skilled operator is capable tocontrol the crane.
He does not even need to usedifferential equations or a cable-length sensor which manycontrol techniques would
require.
So how does he do it?
7/22/2019 Fuzzytech Crane Simulation
12/27
Once he has picked the container, he starts the crane with mediumpower to see how the container sways.
Depending on the reaction, he adjusts motor power to get thecontainer a little behind the crane head.
In this position, maximum speed can be reached with minimumsway.
Getting closer to the target position, the operator reduces motor
power or might even apply negative brake.
With that the container gets a little ahead of the crane head until thecontainer reaches the target position.
Then motor power is increased so that the crane head is over the
target position and sway is zero.
Human-operated
Crane System
7/22/2019 Fuzzytech Crane Simulation
13/27
1. Start with medium power.
2. If you get started and still far away from thetarget, adjust the motor power so the containergets a little behind the crane head.
3. If you are closer to the target, reduce motorspeed so the container gets a little ahead of thecrane head.
4. When the container is very close to the targetposition, power up the motor.
5. When the container is over the target and swayis zero, stop the motor.
Analysis ofOperators actions
7/22/2019 Fuzzytech Crane Simulation
14/27
See if you can write the rules to
control this container crane system
First identify the antecedent variables
Next the consequent variable
Then write the rules according to the
analysis of the operators action in the
previous page.
6 rules can be written- Try?
7/22/2019 Fuzzytech Crane Simulation
15/27
The Control Strategy
1. IF Distance = far AND Angle = zeroTHEN power = pos_medium
2. IF Distance = far AND Angle = neg_smallTHEN power = pos_big
3. IF Distance = far AND Angle = neg_bigTHEN power = pos_medium
4. IF Distance = medium AND Angle = neg_smallTHEN power = neg_medium
5. IF Distance = close AND Angle = pos_smallTHEN power = pos_medium
6. IF Distance = zero AND Angle = zeroTHEN power = zero
7/22/2019 Fuzzytech Crane Simulation
16/27
Fuzzy Controller Design
From what you have studied thus far, lets
design our Fuzzy Controller to solve thisproblem.
What next?
7/22/2019 Fuzzytech Crane Simulation
17/27
Conventional Fuzzy Control
Fuzzification
Inference
Defuzzficatio
n
Anteceden
ts
Consequ
ent
7/22/2019 Fuzzytech Crane Simulation
18/27
Antecedents
Partition or break your antecedents into
several fuzzy sets that can reflect the system
7/22/2019 Fuzzytech Crane Simulation
19/27
For each antecedent, identify the range for the universeof discourse.
Distance Metres or Yards
Angle From -90o to +90o
Break up each antecedent 5 fuzzy sets each and providethe appropriate label that reflect the variables
Distance Angle
too far
zero
closemedium
farneg_big
neg_
small
zeropos_
small
pos_
big
7/22/2019 Fuzzytech Crane Simulation
20/27
Distance
A
ngle
Next design appropriate membership
functions for each fuzzy set and setthem on the universe of each
antecedent
Typical design would be as follows:
7/22/2019 Fuzzytech Crane Simulation
21/27
Similarly for the consequent
Identify the motor power range
Break up into 5 fuzzy sets
Power
neg_high
neg_medium
zeropos_
medium
pos_high
7/22/2019 Fuzzytech Crane Simulation
22/27
Membership functions of the Consequent
Motor Power
7/22/2019 Fuzzytech Crane Simulation
23/27
Next develop the rules
use matrix form
How many rules maximum?
Distance
Ang
le
NB
NS
ZE
PS
PB
Too far zero close med far
7/22/2019 Fuzzytech Crane Simulation
24/27
Rules proposed by
Fuzzy Tech software
7/22/2019 Fuzzytech Crane Simulation
25/27
Inference procedure?
Max-min or (min/max as
described in FuzzyTech)
Max-dot
Etc.
7/22/2019 Fuzzytech Crane Simulation
26/27
Defuzzification
Centroid
Mean of max
7/22/2019 Fuzzytech Crane Simulation
27/27
Try out the simulation exercise