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@ -73,142 +73,7 @@ namespace Esiur.Analysis.Test
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private void FMain_Load(object sender, EventArgs e)
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private void FMain_Load(object sender, EventArgs e)
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{
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{
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//Ki -29:69 Kp -54:121 Kd 29:112
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button3_Click(sender, e);
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var config = new FuzzyChromosome() { KiStart = -29, KiLength = 69, KpStart = -54, KpLength = 121, KdStart = 29, KdLength = 112 };
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double errStart = -0.412312, errEnd = 1, errAccStart = 0.011, errAccEnd = 0.1;
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var lowErr = new ContinuousSet(MembershipFunctions.Descending(errStart, errEnd / 2.0));
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var midErr = new ContinuousSet(MembershipFunctions.Triangular(errStart, errEnd / 2, errEnd));
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var highErr = new ContinuousSet(MembershipFunctions.Ascending(errEnd / 2.0, errEnd));
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var lowAccErr = new ContinuousSet(MembershipFunctions.Descending(errAccStart, errAccEnd / 2.0));
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var midAccErr = new ContinuousSet(MembershipFunctions.Triangular(errAccStart, errAccEnd / 2.0, errAccEnd));
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var highAccErr = new ContinuousSet(MembershipFunctions.Ascending(errEnd / 2.0, errAccEnd));
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var kiSmall = new ContinuousSet(MembershipFunctions.Descending(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1));
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var kiAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
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var kiBig = new ContinuousSet(MembershipFunctions.Ascending((config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
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var kdSmall = new ContinuousSet(MembershipFunctions.Descending(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1));
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var kdAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
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var kdBig = new ContinuousSet(MembershipFunctions.Ascending((config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
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var kpSmall = new ContinuousSet(MembershipFunctions.Descending(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1));
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var kpAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
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var kpBig = new ContinuousSet(MembershipFunctions.Ascending((config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
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var x = Enumerable.Range(0, interval).Select(x => x * 0.01).ToArray();
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var step = Enumerable.Repeat(1, interval).Select(x => (double)x).ToArray();
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step[0] = 0;
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var motor = new TransferFunction(num, denum, 0.01);
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var motorPID = new TransferFunction(num, denum, 0.01);
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var motorFuzzyPID = new TransferFunction(num, denum, 0.01);
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//double Kp = 2, Ki = 0.4, Kd = 0.4;
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double Ki = -1.9181372, Kp = 18.625, Kd = 0.38281253;
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var pid = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
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var fuzzyPID = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
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var sysOut = new double[step.Length];
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var sysOutFuzzyPID = new double[step.Length];
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var sysOutPID = new double[step.Length];
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var pidOut = new double[step.Length];
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var pidOutFuzzy = new double[step.Length];
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var errorOutPID = new double[step.Length];
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var errOut = new double[step.Length];
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var errAccOut = new double[step.Length];
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//var errorAccOut = new double[step.Length];
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var errorOutFuzzy = new double[step.Length];
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var errorOutAccFuzzy = new double[step.Length];
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for (var i = 0; i < step.Length; i++)
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{
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sysOut[i] = motor.Evaluate(step[i]);
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errOut[i] = stability - sysOut[i];
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errAccOut[i] = errOut[i] - (i == 0 ? 0 : errOut[i - 1]);
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sysOutPID[i] = motorPID.Evaluate(step[i] + (i == 0 ? 0 : pidOut[i - 1]));
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sysOutFuzzyPID[i] = motorFuzzyPID.Evaluate(step[i] + (i == 0 ? 0 : pidOutFuzzy[i - 1]));
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errorOutPID[i] = (stability - sysOutPID[i]);
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errorOutFuzzy[i] = (stability - sysOutFuzzyPID[i]);
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errorOutAccFuzzy[i] = (errorOutFuzzy[i] - (i == 0 ? 0 : errorOutFuzzy[i - 1]));
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pidOut[i] = pid.Evaluate(errorOutPID[i]);
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pidOutFuzzy[i] = fuzzyPID.Evaluate(errorOutFuzzy[i]);
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var ki = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
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{
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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var kp = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
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{
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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var kd = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
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{
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdSmall),
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errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdAvg),
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errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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fuzzyPID.InputCoefficients[0] = ki;
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fuzzyPID.InputCoefficients[1] = kp;
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fuzzyPID.InputCoefficients[1] = kd;
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}
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Debug.WriteLine($"Error Values Min: {errOut.Min()} Max: {errOut.Max()} ");
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Debug.WriteLine($"Error Acc Values Min: {errAccOut.Min()} Max: {errAccOut.Max()} ");
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formsPlot1.Plot.AddScatter(x, sysOut, Color.Red);
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formsPlot1.Plot.AddScatter(x, sysOutPID, Color.Blue);
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formsPlot1.Plot.AddScatter(x, sysOutFuzzyPID, Color.Green);
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formsPlot1.Refresh();
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}
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}
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@ -312,7 +177,7 @@ namespace Esiur.Analysis.Test
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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}, MamdaniDefuzzifierMethod.CenterOfGravity, config.KiStart * 0.1, (config.KiStart + config.KiLength) * 0.1, 0.5);
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if (double.IsNaN(ki))
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if (double.IsNaN(ki))
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return double.MaxValue;
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return double.MaxValue;
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@ -328,7 +193,7 @@ namespace Esiur.Analysis.Test
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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}, MamdaniDefuzzifierMethod.CenterOfGravity, config.KpStart * 0.1, (config.KpStart + config.KpLength) * 0.1, 0.5);
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if (double.IsNaN(kp))
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if (double.IsNaN(kp))
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return double.MaxValue;
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return double.MaxValue;
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@ -344,7 +209,7 @@ namespace Esiur.Analysis.Test
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdAvg),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
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errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
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}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
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}, MamdaniDefuzzifierMethod.CenterOfGravity, config.KdStart * 0.1, (config.KdStart + config.KdLength) * 0.1, 0.5);
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if (double.IsNaN(kd))
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if (double.IsNaN(kd))
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return double.MaxValue;
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return double.MaxValue;
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@ -457,10 +322,7 @@ namespace Esiur.Analysis.Test
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private void button1_Click(object sender, EventArgs e)
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private void button1_Click(object sender, EventArgs e)
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{
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{
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var genetic = new Genetic<FuzzyChromosome>(10, k =>
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var genetic = new Genetic<FuzzyChromosome>(100, k =>
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{
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{
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if (float.IsNaN(k.KiStart)
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if (float.IsNaN(k.KiStart)
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|| float.IsNaN(k.KiLength)
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|| float.IsNaN(k.KiLength)
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