📄 demo.doc
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Convention
The following conventions are used throughout this document.
'Enter' means the Enter key or the Return key.
Type 'key' means press the specified key without 'Enter'.
Press F? means press the specified function key without 'Enter'.
Enter means type in the specified text and followed by 'Enter'
key.
Select/Use an option:
use cursor keys to move the highlighted option and press
'Enter', or type the upper-cased character on the left.
GAF is not case sensitive, use either upper or lower cased key.
Using The Menu
The GAF system menu, at the top of the screen, is the primary user interface
to the system. System menu provides sub-menu function selection (function
menus): File, Run, Display, Control, Adapt, Method, Segment, Feedback,
Eval, and Help. Use the first character of each selection or use cursor
keys (right/left arrows) to select the sub-menu. When a function menu is
selected a pull down menu appears to provide function selection. To
select a function either by the character on the left of that function or
move the cursor with up/down arrow keys and then "Enter". When a function
is selected, further menu selection or data entry menu may be provided by
that function. Press ESC in function menu will return to system menu.
Press ESC under system menu will bring run function menu, except when the
system menu was ESCaped from any of the running screen (i.e. from adapting
or simulation). Please refer GAF.DOC for details. The following steps
are typical for function selection under simulation or adapting.
press "ESC" to escape back to system menu
select desired function menu (see above)
select desired function (see above)
press "ESC" again under system menu to go back
Simulation
This simple example demonstrates the application of the fuzzy logic to
control a motor based on its angular position feedback. Lets assume that
this is a robot arm, and its arm extension limit (in angular position) is
from 0 degree to 70 degree. The inputs to the control loop are the
position, position error, and the speed, the output is the current to the
motor. The example also demonstrates that using fuzzy logic to simulate
the feedback loop, e.g. the position feedback and the angular speed. The
file "robotarm.gaf" defines the control loop, and the file "robotarm.fbk"
defines the feedback loop.
Run Simulation
After start the demo, you'll find the system menu is at the top of the
screen. Select run menu by typing 'R', then select "simulation mode"
by either type 'S' or move high lighted cursor to "simulation mode" and
press 'Enter'. After simulation mode is selected, GAF displays the
control segment on the screen and waits for user input. Please refer to
GAF.DOC for details of the display windows. Type 'F' to start the
simulation. You should see the trend plots of inputs and outputs on the
right and the rules and firing status on the left of the screen.
Reset the system
Press function key F7 to reset the system. The system reset is defined
by the INITIALIZATION declaration in all segments of the system.
Type 'F' again to run the simulation.
View the feedback loop
Now switch to the feedback loop by pressing F3, the screen displays the
feedback segment. Press F7 to reset the system, and then type 'F'.
Now watch the plot of the inputs and the outputs for the feedback loop.
Stepping through
Let's switch back to the control loop by pressing F3 twice, and reset it
by F7. Now press 'Enter' to see the demo program goes one step. The
program allows you to do one step by 'Enter' or multiple steps by typing
2 to 9, or 10 steps by typing '0'. Type '0' and watch the program goes
through 10 steps and note different rules are fired. At any time type
'F' will bring you to the end of the plot frame.
Continuous mode
Press 'C' to run the simulation continuously. You can stop continuous
mode by pressing 'C' again or ESCape (press ESC) back to system
menu. While in continuous mode press F7 to reset the system.
Change variable value
Stop continuous mode by pressing 'C'. Now let's change the simulation
from raising the arm to lowering the arm. Press F7 and then ESC to
escape back to system menu. Press 'S' to select segment menu. The
segment menu allows you to switch segment and change characteristics
of the segment. Switch to feedback segment by selecting "segment
number" under segment menu, and enter '1' for feedback segment.
Select segment menu again, and select "set input value". GAF pops all
inputs in a menu beneath the segment menu, select "REFERENCE"
input and enter its new value to 0. Select segment menu one more time
to change the input variable "POSITION" value to 70 (from "set input
value"). Now get back to the simulation by pressing ESC, press F3 to
switch back to control segment, and start simulation by stepping through
it. Note that you can also change the "POSITION" value from the
control segment (segment 0).
View the plot
From system menu type 'D' to select display menu. The display menu
allows you to rearrange the display windows. Let's select "select plot
only mode" by typing '5', and then escape back to simulation. GAF
should redraw the screen with trend plot takes most of the screen. Run
simulation by hiting F7 and then 'F'.
View the combined result
From Display menu select "select whole display mode". The right
portion of the screen splits into two parts, the upper half shows the
plot, and the lower half displays the combined result for the output.
The combined result shows the trapezoid result of all fired rules (rules
generate non-zero output). Rerun the simulation by pressing F7, and
then 'F'. Now, the combined result tells you about the firing results of
all rules and the defuzzified crisp output (the current of the motor)
from all fired rules.
View details about the fuzzy inference
The above exercise only allows you to view the combined result of the
output. GAF also allows you to examine the firing details of the rules.
This feature along with the stepping mode is the best way to tuneup or
debug the control segment. From the segment menu, select "display rule
firing", GAF highlights the first rule by using the left column of the
text window. Use down arrow key to move to rule 5 and press 'Enter' to
select it. Go back to the simulation, you'll find the selected rule's
fuzzy sets are displayed to the left of the combined result. Note that
each fuzzy set has the same color as the text window. Try previous
exercises to view the changes of the fuzzy rule firing status.
Disable rules
GAF allows user to disable individual rule for testing fuzzy segment.
Let's disable rule 10, this will effectively break the control system.
Since there is no rule to respond when the POS_ERROR is
VERY_LARGE, so after system reset (press F7) there will be no output
from the control segment. From segment menu select "disable rule",
GAF highlights the rule ID 0 on the left of the screen. Press 'End' to
move the highlight cursor to rule 10, and then type 'Enter'. Now restart
the simulation by pressing F7 then 'F'. You should see the rule 10 is
marked with 'X' to indicate it's been disabled, and also that there is no
response to the position of the robot arm.
Enable rules
There are two options under segment menu allow you to enable rule(s).
The "enable all rules" option enables all rules in this segment. The
"enable rule" enables the selected rule. So, type 'A' under segment
menu to enable rule 10.
Change sampling rate
Another important feature in GAF is that you can tune your system by
trying different sampling rate (or cycle time defined in each segment).
From control menu select "sim schedule rate", GAF prompts for new
rate. Enter 0.2 (in second) and restart the simulation.
Increment/decrement sampling rate
An easy way to change the simulated sampling rate is to use the '+' and
'-' keys. Press '+' each time will cause the sample rate to increase
0.005 second, and press '-' will decrease the sample rate by 0.005
second. The amount of increment/decrement (default is 0.005 second)
can be changed through the control menu's "Increment value" option.
Now put the simulation in continuous mode by 'C', reset it by F7 and
then use '+' and '-' keys to adjust the sample rate to find out what's
the max stable rate of the control loop.
Change output gain
You can change the gain of the output, from segment menu's "set output
gain" option. The default gain is 1.0.
Check individual segment
This feature allows you to examine one segment at a time. Let's
examine the feedback loop's response at a constant motor current. Press
F3 to switch to the feedback segment. From run menu select "check
segment". Then from segment menu change the value of input variable
"CURRENT" to 1.0. Run the simulation by typing 'F' to see the
response of constant current input.
Getting online help
Press F1 to get online help.
Display the system limits
Press F2 to see the system limits.
View segment information
Press F4 to see the variable definition, initialization and normal
functions, and other information for the selected display segment.
View symbol definition
Press F5 to see the fuzzy set symbols' definition for this segment.
View preset definition
Press F6 to view the preset definition for this segment.
Set new plot time frame
The default plot frame period is five seconds (except in sim clock mode),
this can be changed through display menu's "plot duration" option.
View local variables
The default display mode is to display IN, OUT, and INOUT variables,
the LOCAL variables are not displayed. Use "display local variable"
option in display menu to enable/disable LOCAL variables.
Quit the program
Press 'Alt-Q' to quit the program under simulation or select "quit"
option from run menu.
Adapting the Fuzzy Segment
The genetic adapt mode is an offline adaptation mode. While fuzzy logic
mimics the human's imprecise reasoning, the genetic algorithm mimics the
evolution of the nature. The genetic algorithm uses randomization
techniques to reach local optimum without exhausting searching through the
solution state space. With randomization, genetic algorithm is also
capable of escaping from local optimum and hopping into a new and better
state. Apply genetic algorithm in fuzzy control eliminates problems
associated with fuzzy system. GAF uses genetic algorithm to derive proper
rules and fuzzy sets from the initial rules. By changing, adding, deleting
rules and fuzzy membership sets of the fuzzy system, the genetic algorithm
automatically adapts and optimizes the fuzzy control system.
The adapting example is built on top of the simulation example, by adding
a third evaluation segment. The file "robotarm.evl" defines the evaluation
segment.
Start Adapting
From system menu, type 'R' to bring up run menu. Select "adapt
mode" by pressing 'A'. GAF starts adapting the control loop and
displays the control segment along with adapt status on the top of the
screen.
Pause every iteration
Press Alt-P to halt the adapting after each iteration. Press 'C' to
continue next iteration. Press Alt-C to switch to continuous mode.
Pause every cycle
Press Alt-P to stop the adapting after each cycle. Press 'C' to continue
next cycle. Press Alt-C to switch to continuous mode.
Change size of gene pool
Press 'Esc' while in continuous adapting, GAF brings up the system
menu. Select adapt menu by type 'A'. From adapt menu select 'max
best items', and enter a new pool size. This will change the number of
genes will be saved (and evaluated) by GAF.
Change minimum score
Again, from adapt menu, select "minimum score", GAF prompts for
new minimum value. Enter 0.5, this tells GAF to accept all evaluation
results ,which are greater or equal than 0.5. The default of the
minimum score is 0.6.
Change method
The method menu provides user to control the algorithm of genetic
adaptation. Select "adding rule" from method menu, enter 0 for its new
weight. With zero weight, GAF will not generate (adding) new rule into
the control loop.
Print the result
Select 'File' menu from the system menu, and type 'A' to generate
report for all genes in the gene pool. The result will be saved in the
adaptlog.rpt file of the current directory.
Generate statistic report
Again type 'S' (generate statistic log) from 'File' menu, GAF produces
a statistic report file with the file name specified by 'statistic to'
at the bottom of the menu. The log includes statistics for all methods.
Based on the statistic you may want to adjust the weight of the methods.
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