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But not perfectly occasionally, I got the message Invalid Input. In the fuzzyTECH manual, it documents the serial data stream as being the decimal representative of the value with an optional or - at the start, followed by the ASCII decimal representation of the number. Valid numbers are
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123 +123 -123 +1.23 -1.23 +1.23E-4
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where in the last example the E represents 10 to the power of. I found that if I always sent data with a leading sign and three data digits, the Invalid Input message would go away. In the serial input data handler, I simpli ed it by not having exponents and by truncating off fractional data I just handled the integer values of the fuzzyTECH input. When I rst designed this application, I copied the temperature controller application source code that comes with the product almost exactly. This was a mistake based on how the two applications work. The input for the fuzzy controller was the difference between the input control and the motor control PWM. This value, from 20 to 20 was converted into the data string above and passed to fuzzyTECH. The output was a PWM range based on the error rate. When I started the application, I found that I could not regulate the speed adequately. While not a fully out-of-control situation, I did have wild oscillations that could not be damped down by changing the rules. The difference between the two systems was the amount of inertia that was being controlled in the thermometric example, temperature changes taking place over many seconds; in the fan controller, changes in speed could be implemented in less than a second. While the fuzzy logic controller could keep the oscillations from becoming unbounded, there was still a 20 to 30 percent change in the fan s speed each second. The solution to this problem was to change the operation of the fuzzy logic system. While I still retained the input as the difference between the set speed and the actual speed, the output was changed to output differences in the PWM duty cycle from the actual PWM duty cycle. The application code was modeled as
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main() { initialize(); PWM = 50 percent; // Fuzzy Logic Fan Motor Controller
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Initialize the Hardware Initialize the PWM to a 50% duty cycle
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While (1 == 1) { Dlay ( ); Speed error = ADCinput countACT; PWM = PWM + FuzzyMod(speed error);
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Fuzzy logic fan control rules for speed errors.
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If (PWM PWM = else if PWM = } } //
<0) 0; (PWM > 200) 200;
Keep PWM within Valid Range
End Fuzzy Logic Fan Motor Controller
The speed error fuzzyTECH input was given the four rules shown in Fig. 21.59. In this set of rules, I identi ed difference ranges (or patches) for too fast, too slow, and just right. These were matched with the output rules shown in Fig. 21.60. For the input, I used a range of 20 to 20, where this value is the difference in counts, to a maximum of 200, between the ADC input (desired speed) and the counter input (actual speed). The change in PWM output is set to the range of 20 to 20. Each increase of one digit resulted in about a 1 percent in change of fan speed. When I started this fuzzy logic system with fuzzyTECH, I found an immediate improvement in the performance of the system. Rather than oscillating between 20 and 30 percent from the target, I found that the motor was regulated to within 8 percent. While 8 percent was a lot better, I thought I could do even better. My primary strategies were cutting the delay interval by 4 (down to a four times per second sample) and moving the input and output rules. I found that these simple changes resulted in the system being able to keep the fan motor running to within 2 percent; although it occasionally extended to 3 or 4 percent, as you can see in Fig. 21.61. In this gure, the light-colored
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