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Diodes Because the PIC is sensitive to electrical spikes (may cause a reset or lock-up), we place diodes across the collector-emitter junction of each transistor (Q1 to Q4). These diodes snub any electrical spikes caused by switching the motor windings on and off. The PICBASIC compiler program is as follows:
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Fuzzy Logic Light Tracker Program start: low 0 low 1 Pin 0 low Pin 1 low Read first CdS sensor Read second CdS sensor If equal, do nothing If greater, check how much greater If lesser, check how much lesser
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if b0 > b1 then greater if b0 < b1 then lesser greater: b2 = b0 b1 goto start lesser: b2 = b1 b0 goto start cw: high 0 pause 100 goto start ccw: high 1 pause 100 goto start
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Greater routine Find the difference Is it within range If not, go to CW In range, do again Lesser routine Find the difference Is it within range If not, go to CCW Do again
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Turn the sensor array CW Turn on H-bridge Let it turn for a moment Check again
Turn the sensor array CCW Turn on H-bridge Let it turn a moment Check again
Operation When running, the light tracker will follow a light source. If both CdS cells are approximately evenly illuminated, the tracker does nothing. To test the light tracker, cover one CdS sensor with your finger. This should activate the gearbox motor and the shaft should begin to rotate. If the shaft rotates in the opposite direction of the light source, reverse either the sensor input pins or the output pins to the Hbridge, but not both.
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6.35 H-bridge function and circuit schematic
Not fuzzy output The output of our fuzzy light tracker is binary. The motor is either on or off, rotating CW or CCW. In many cases you would want the output to be fuzzy also. For instance, let us say you are making a fuzzy controller for an elevator. You would want the elevator to start and stop gradually (fuzzy) not abruptly as in binary (on/off). Could we change the output of our light tracker and make it fuzzy Yes. Instead of simply switching the motor on, we could feed a pulse-width modulation (PWM) signal that can vary the motor s speed. Ideally the motor s speed would be in proportion to the difference (in resistance) of the two CdS cells. A large difference would produce a faster speed than would a small difference. The motor speed would change dynamically (in real time) as the tracker brings both CdS cells to equal illumination. This output program may be illustrated using fuzzy logic graphics, groups, and membership sets. In this particular application creating a fuzzy output for this demonstration light tracker unit is overkill.
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If you want to experiment, begin by using the pulsout and pwm commands to vary the DC motor speed. Neural sensors (logic) With a small amount of programming, we can change our fuzzy logic sensors (CdS photocells) to neural sensors. Neural networks are an expansive topic. We will limit ourselves to one small example. For those who want to further pursue study into neural networks, I recommend a book I ve written titled Understanding Neural Networks (Prompt, Indianapolis, 1998, ISBN 0-7906-1115-5). To create neural sensors, we will take the numeric resistive reading from each sensor, multiply it by a weight factor, and then sum the results. The results are then compared to a tri-level threshold value (see Fig. 6.36). Thus our small program and sensors are performing all the functions expected in a neural network. We may even be pioneering a neural first, by applying a multivalue threshold scheme. Do multivalue thresholds exist in nature (biological systems) The answer is yes. For instance, an itch is an extremely low level of pain, and the sensation of burning can be felt when sensing something ice cold or hot.
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