Raw data for evolving AVC controller
<p>An Excel spreadsheet generated by the genetic algorithm (GA) program "GenAlgor4_1_5Arduino.m", which calls the Arduino Due program "ArduinoMatlabControllerV6_2.ino" to impliment hardware-in-the-loop active vibration control.</p>
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<p>The spreadsheet contains raw data from a run of 250 generations of the GA optimising controller coefficients for active vibration control (AVC). The run in this file was for a population of 50 individuals, each of 60 x 4 bit genes.</p>
<p>Breeding was by elite selection with double point crossover and 1% mutation.</p>
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<p>The first six rows contain the GA set up:</p>
<p> row 1: population size</p>
<p> row 2: number of genes per chromosome (population member)</p>
<p> row 3: number of bits per gene</p>
<p> row 4: breeding selection type (1=elite, 2=roulette)</p>
<p> row 5: breeding crossover type (1=single point, 2=double point or circular)</p>
<p> row 6: mutation rate</p>
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<p>Rows 7 onwards give population genes and AVC results in each generation, sorted in order of performance index (PI) = fitness - cost</p>
<p>1st generation and thereafter every 10th generation are given in full. Other generations’ results are given only for the best, middle and worst individuals only.</p>
<p>Each row gives the value of each gene, a number 0-15 for 4 bit genes, in columns A-BH for 60 genes. This is followed by three columns containing the AVC results: </p>
<p> column BI: performance index = fitness - cost</p>
<p> column BJ: amplitude returned from Arduino</p>
<p> column BK: cost</p>
<p> fitness = amplitude reduction - cost</p>
<p> amplitude reduction = uncontrolled - AVC amplitude </p>
<p> cost = sum of delay line coefficients × a constant</p>
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