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Soft Computing

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This commit is contained in:
Ahmed Zamil 2022-11-06 13:25:49 +03:00
parent f1d5b0a38b
commit 2844eb60ec
11 changed files with 790 additions and 430 deletions
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72
Esiur.Analysis.Test/FMain.Designer.cs generated
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namespace Esiur.Analysis.Test
{
partial class FMain
{
/// <summary>
/// Required designer variable.
/// </summary>
private System.ComponentModel.IContainer components = null;
/// <summary>
/// Clean up any resources being used.
/// </summary>
/// <param name="disposing">true if managed resources should be disposed; otherwise, false.</param>
protected override void Dispose(bool disposing)
{
if (disposing && (components != null))
{
components.Dispose();
}
base.Dispose(disposing);
}
#region Windows Form Designer generated code
/// <summary>
/// Required method for Designer support - do not modify
/// the contents of this method with the code editor.
/// </summary>
private void InitializeComponent()
{
this.formsPlot1 = new ScottPlot.FormsPlot();
this.button1 = new System.Windows.Forms.Button();
this.SuspendLayout();
//
// formsPlot1
//
this.formsPlot1.Location = new System.Drawing.Point(57, 47);
this.formsPlot1.Margin = new System.Windows.Forms.Padding(5, 4, 5, 4);
this.formsPlot1.Name = "formsPlot1";
this.formsPlot1.Size = new System.Drawing.Size(1006, 576);
this.formsPlot1.TabIndex = 0;
//
// button1
//
this.button1.Location = new System.Drawing.Point(12, 316);
this.button1.Name = "button1";
this.button1.Size = new System.Drawing.Size(85, 31);
this.button1.TabIndex = 1;
this.button1.Text = "button1";
this.button1.UseVisualStyleBackColor = true;
this.button1.Click += new System.EventHandler(this.button1_Click);
//
// FMain
//
this.AutoScaleDimensions = new System.Drawing.SizeF(8F, 20F);
this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font;
this.ClientSize = new System.Drawing.Size(1175, 658);
this.Controls.Add(this.button1);
this.Controls.Add(this.formsPlot1);
this.Name = "FMain";
this.Text = "PID Controller with Fuzzy";
this.Load += new System.EventHandler(this.FMain_Load);
this.ResumeLayout(false);
}
#endregion
private ScottPlot.FormsPlot formsPlot1;
private Button button1;
}
}

345
Esiur.Analysis.Test/FMain.cs
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using Esiur.Analysis.DSP;
using Esiur.Analysis.Fuzzy;
using Esiur.Analysis.Optimization;
using Esiur.Analysis.Signals;
using Esiur.Analysis.Units;
using Microsoft.VisualBasic.Logging;
using ScottPlot;
using ScottPlot.Drawing.Colormaps;
using System.Security.Cryptography;
using Esiur.Analysis.Statistics;
using System.Diagnostics;
namespace Esiur.Analysis.Test
{
public partial class FMain : Form
{
public FMain()
{
InitializeComponent();
//var outage = Capacity.ComputeOutage(20000000, new Capacity.CSI[]
//{
// new Capacity.CSI(PowerUnit.FromDb(20), 0.1),
// new Capacity.CSI(PowerUnit.FromDb(15), 0.15),
// new Capacity.CSI(PowerUnit.FromDb(10), 0.25),
// new Capacity.CSI(PowerUnit.FromDb(5), 0.25),
// new Capacity.CSI(PowerUnit.FromDb(0), 0.15),
// new Capacity.CSI(PowerUnit.FromDb(-5), 0.1),
//});
var outage = Capacity.ComputeOutage(1, new Capacity.CSI[]
{
new Capacity.CSI(PowerUnit.FromDb(30), 0.2),
new Capacity.CSI(PowerUnit.FromDb(20), 0.3),
new Capacity.CSI(PowerUnit.FromDb(10), 0.3),
new Capacity.CSI(PowerUnit.FromDb(0), 0.2),
});
var low = new ContinuousSet(MembershipFunctions.Descending(20, 40));
var mid = new ContinuousSet(MembershipFunctions.Triangular(20, 40, 60));
var high = new ContinuousSet(MembershipFunctions.Ascending(40, 60));
var bad = new ContinuousSet(MembershipFunctions.Descending(0, 30));
var ok = new ContinuousSet(MembershipFunctions.Triangular(20, 50, 80));
var excelent = new ContinuousSet(MembershipFunctions.Ascending(70, 100));
var small = new ContinuousSet(MembershipFunctions.Descending(100, 200));
var avg = new ContinuousSet(MembershipFunctions.Triangular(100, 200, 300));
var big = new ContinuousSet(MembershipFunctions.Ascending(200, 300));
//var speedIsLowThenSmall = new FuzzyRule("Low=>Small", low, small);
double rating = 80;
for (double temp = 60; temp < 100; temp++)
{
var v = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
temp.Is(low).And(rating.Is(bad)).Then(small),
temp.Is(mid).And(rating.Is(ok)).Then(avg),
temp.Is(high).And(rating.Is(excelent)).Then(big),
}, MamdaniDefuzzifierMethod.CenterOfGravity, 100, 300, 1);
}
}
private void FMain_Load(object sender, EventArgs e)
{
var lowErr = new ContinuousSet(MembershipFunctions.Descending(-5, 4.5));
var midErr = new ContinuousSet(MembershipFunctions.Triangular(-4, 6.5, 16.5));
var highErr = new ContinuousSet(MembershipFunctions.Ascending(8, 18));
var lowAccErr = new ContinuousSet(MembershipFunctions.Descending(0, 0.02));
var midAccErr = new ContinuousSet(MembershipFunctions.Triangular(0.02, 0.04, 0.06));
var highAccErr = new ContinuousSet(MembershipFunctions.Ascending(0.04, 0.06));
var small = new ContinuousSet(MembershipFunctions.Descending(0.1, 0.5));
var avg = new ContinuousSet(MembershipFunctions.Triangular(0.1, 0.5, 1.1));
var big = new ContinuousSet(MembershipFunctions.Ascending(-10, 1.1));
var x = Enumerable.Range(0, 1000).Select(x => x * 0.01).ToArray();
var step = Enumerable.Repeat(1, 1000).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(new double[] { 1, 2 }, new double[] { 1, 1, 2 }, 0.01);
var motorPID = new TransferFunction(new double[] { 1, 2 }, new double[] { 1, 1, 2 }, 0.01);
var motorFuzzyPID = new TransferFunction(new double[] { 1, 2 }, new double[] { 1, 1, 2 }, 0.01);
//double Kp = 2, Ki = 0.4, Kd = 0.4;
double Ki = -1.9181372, Kp = 18.625, Kd = 0.38281253;
var pid = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var fuzzyPID = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var sysOut = new double[step.Length];
var sysOutFuzzyPID = new double[step.Length];
var sysOutPID = new double[step.Length];
var pidOut = new double[step.Length];
var pidOutFuzzy = new double[step.Length];
var errorOutPID = new double[step.Length];
var errOut = new double[step.Length];
var errAccOut = new double[step.Length];
//var errorAccOut = new double[step.Length];
var errorOutFuzzy = new double[step.Length];
var errorOutAccFuzzy = new double[step.Length];
for (var i = 0; i < step.Length; i++)
{
sysOut[i] = motor.Evaluate(step[i]);
errOut[i] = step[i] - sysOut[i];
errAccOut[i] = errOut[i] - (i == 0 ? 0 : errOut[i - 1]);
sysOutPID[i] = motorPID.Evaluate(step[i] + (i == 0 ? 0 : pidOut[i - 1]));
sysOutFuzzyPID[i] = motorFuzzyPID.Evaluate(step[i] + (i == 0 ? 0 : pidOutFuzzy[i - 1]));
errorOutPID[i] = (step[i] - sysOutPID[i]);
errorOutFuzzy[i] = (step[i] - sysOutFuzzyPID[i]);
errorOutAccFuzzy[i] = (errorOutFuzzy[i] - (i == 0 ? 0 : errorOutFuzzy[i - 1]));
pidOut[i] = pid.Evaluate(errorOutPID[i]);
pidOutFuzzy[i] = fuzzyPID.Evaluate(errorOutFuzzy[i]);
var k = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(small),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(small),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(avg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(small),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(avg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(big),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(avg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(big),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(big),
}, MamdaniDefuzzifierMethod.CenterOfGravity, 0, 1, 0.05);
fuzzyPID.InputCoefficients[1] = k;
fuzzyPID.InputCoefficients[1] = k;
fuzzyPID.InputCoefficients[1] = k;
}
Debug.WriteLine($"Error Values Min: {errOut.Min()} Max: {errOut.Max()} ");
Debug.WriteLine($"Error Acc Values Min: {errAccOut.Min()} Max: {errAccOut.Max()} ");
formsPlot1.Plot.AddScatter(x, sysOut, Color.Red);
formsPlot1.Plot.AddScatter(x, sysOutPID, Color.Blue);
formsPlot1.Plot.AddScatter(x, sysOutFuzzyPID, Color.Green);
formsPlot1.Refresh();
}
struct KK
{
public float Ki;
public float Kp;
public float Kd;
public override string ToString()
{
return $"Ki {Ki} Kp {Kp} Kd {Kd}";
}
}
struct FuzzyChromosome
{
public sbyte KiInputErrPosition;
public sbyte KiInputErrScale;
public sbyte KiInputErrAccPosition;
public sbyte KiInputErrAccScale;
public sbyte KiOutputPosition;
public sbyte KiOutputScale;
}
private double CalculateFuzzyPIDStepError(FuzzyChromosome config, double errStart, double errEnd)
{
var errPos = config.KiInputErrPosition * 0.1;
var errScale = config.KiInputErrPosition * 0.1;
var lowErr = new ContinuousSet(MembershipFunctions.Descending(config.KiInputErrPosition * 0.1, config.kiLowStart * 0.1 + Math.Abs(config.kiLowEnd * 0.1)));
var midErr = new ContinuousSet(MembershipFunctions.Triangular(config.KiInputErrPosition * 0.1, config.kiMidStart * 0.1 + Math.Abs(config.kiMidMid * 0.1), config.kiMidStart * 0.1 + Math.Abs(config.kiMidMid * 0.1) + Math.Abs(config.kiMidEnd * 0.1)));
var highErr = new ContinuousSet(MembershipFunctions.Ascending(config.KiInputErrPosition * 0.1, config.kiHiStart * 0.1 + Math.Abs(config.kiHiEnd * 0.1)));
var lowAccErr = new ContinuousSet(MembershipFunctions.Descending(config.KiInputErrAccPosition * 0.1, Math.Abs(config.kiLowAccStart * 0.1) + Math.Abs(config.kiLowAccEnd * 0.1)));
var midAccErr = new ContinuousSet(MembershipFunctions.Triangular(config.KiInputErrAccPosition * 0.1, Math.Abs(config.kiMidAccStart * 0.1) + Math.Abs(config.kiMidAccMid * 0.1), config.kiMidAccStart * 0.1 + Math.Abs(config.kiMidAccMid * 0.1) + Math.Abs(config.kiMidAccEnd * 0.1)));
var highAccErr = new ContinuousSet(MembershipFunctions.Ascending(config.KiInputErrAccPosition * 0.1, config.kiHiAccStart * 0.1 + Math.Abs(config.kiHiAccEnd * 0.1)));
var small = new ContinuousSet(MembershipFunctions.Descending(config.kiSmallStart * 0.1, config.kiSmallStart * 0.1 + Math.Abs(config.kiSmallEnd * 0.1)));
var avg = new ContinuousSet(MembershipFunctions.Triangular(config.kiAvgStart * 0.1, config.kiAvgStart * 0.1 + Math.Abs(config.kiAvgMid * 0.1), config.kiAvgStart * 0.1 + Math.Abs(config.kiAvgMid * 0.1) + Math.Abs(config.kiAvgEnd * 0.1)));
var big = new ContinuousSet(MembershipFunctions.Ascending(config.kiBigStart * 0.1, config.kiBigStart * 0.1 + Math.Abs(config.kiBigEnd * 0.1)));
double Ki = -1.9181372, Kp = 18.625, Kd = 0.38281253;
var step = Enumerable.Repeat(1, 1000).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(new double[] { 1, 2 }, new double[] { 1, 1, 2 }, 0.01);
var fuzzyPID = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var sysOutFuzzyPID = new double[step.Length];
var pidOut = new double[step.Length];
var pidOutFuzzy = new double[step.Length];
var errorOutFuzzy = new double[step.Length];
var errorOutAccFuzzy = new double[step.Length];
for (var i = 0; i < step.Length; i++)
{
sysOutFuzzyPID[i] = motor.Evaluate(step[i] + (i == 0 ? 0 : pidOutFuzzy[i - 1]));
errorOutFuzzy[i] = (step[i] - sysOutFuzzyPID[i]);
errorOutAccFuzzy[i] = (errorOutFuzzy[i] - (i == 0 ? 0 : errorOutFuzzy[i - 1]));
pidOutFuzzy[i] = fuzzyPID.Evaluate(errorOutFuzzy[i]);
var k = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(small),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(small),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(avg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(small),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(avg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(big),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(avg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(big),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(big),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -100, 100, 0.5);
fuzzyPID.InputCoefficients[1] = k;
//fuzzyPID.InputCoefficients[1] = k;
//fuzzyPID.InputCoefficients[1] = k;
}
return errorOutFuzzy.RMS();
}
private double CalculatePIDStepError(double Kd, double Kp, double Ki)
{
var step = Enumerable.Repeat(1, 1000).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(new double[] { 1, 2 }, new double[] { 1, 1, 2 }, 0.01);
var sysOutPID = new double[step.Length];
var pidOut = new double[step.Length];
var errorOutPID = new double[step.Length];
var pid = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
for (var i = 0; i < step.Length; i++)
{
sysOutPID[i] = motor.Evaluate(step[i] + (i == 0 ? 0 : pidOut[i - 1]));
if (double.IsInfinity(sysOutPID[i]))
Console.WriteLine();
errorOutPID[i] = (step[i] - sysOutPID[i]);
if (double.IsNaN(errorOutPID[i]))
Console.WriteLine();
pidOut[i] = pid.Evaluate(errorOutPID[i]);
if (double.IsInfinity(pidOut[i]))
Console.WriteLine();
}
return errorOutPID.RMS();
}
private void button1_Click(object sender, EventArgs e)
{
//var gen = new Genetic<KK>(100, k =>
//{
// if (float.IsNaN(k.Ki) || float.IsNaN(k.Kp) || float.IsNaN(k.Kd))
// return (double.MaxValue);
// var r = CalculatePIDStepError(k.Kd, k.Kp, k.Ki);
// if (double.IsNaN(r))
// Console.WriteLine();
// return r;
//});
var gen = new Genetic<KKFF>(100, k =>
{
if (float.IsNaN(k.kiAvgEnd)
|| float.IsNaN(k.kiAvgMid)
|| float.IsNaN(k.kiAvgStart)
|| float.IsNaN(k.kiBigEnd)
|| float.IsNaN(k.kiBigStart)
|| float.IsNaN(k.kiHiAccEnd)
|| float.IsNaN(k.kiHiAccStart)
|| float.IsNaN(k.kiHiEnd)
|| float.IsNaN(k.kiHiStart)
|| float.IsNaN(k.kiLowAccEnd)
|| float.IsNaN(k.kiLowAccStart)
|| float.IsNaN(k.kiLowEnd)
|| float.IsNaN(k.kiLowStart)
|| float.IsNaN(k.kiMidAccEnd)
|| float.IsNaN(k.kiMidAccMid)
|| float.IsNaN(k.kiMidAccStart)
|| float.IsNaN(k.kiMidEnd)
|| float.IsNaN(k.kiMidMid)
|| float.IsNaN(k.kiMidStart)
|| float.IsNaN(k.kiSmallEnd)
|| float.IsNaN(k.kiSmallStart))
return (double.MaxValue);
var r = CalculateFuzzyPIDStepError(k);
if (double.IsNaN(r))
Console.WriteLine();
return r;
});
var ev = gen.Evaluate(1000);
Console.WriteLine(ev);
}
}
}

169
Esiur.Analysis.Test/FSoft.Designer.cs generated Normal file
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namespace Esiur.Analysis.Test
{
partial class FSoft
{
/// <summary>
/// Required designer variable.
/// </summary>
private System.ComponentModel.IContainer components = null;
/// <summary>
/// Clean up any resources being used.
/// </summary>
/// <param name="disposing">true if managed resources should be disposed; otherwise, false.</param>
protected override void Dispose(bool disposing)
{
if (disposing && (components != null))
{
components.Dispose();
}
base.Dispose(disposing);
}
#region Windows Form Designer generated code
/// <summary>
/// Required method for Designer support - do not modify
/// the contents of this method with the code editor.
/// </summary>
private void InitializeComponent()
{
this.formsPlot1 = new ScottPlot.FormsPlot();
this.button1 = new System.Windows.Forms.Button();
this.formsPlot2 = new ScottPlot.FormsPlot();
this.formsPlot3 = new ScottPlot.FormsPlot();
this.formsPlot4 = new ScottPlot.FormsPlot();
this.button2 = new System.Windows.Forms.Button();
this.textBox1 = new System.Windows.Forms.TextBox();
this.button3 = new System.Windows.Forms.Button();
this.button4 = new System.Windows.Forms.Button();
this.textBox2 = new System.Windows.Forms.TextBox();
this.SuspendLayout();
//
// formsPlot1
//
this.formsPlot1.Location = new System.Drawing.Point(14, 47);
this.formsPlot1.Margin = new System.Windows.Forms.Padding(5, 4, 5, 4);
this.formsPlot1.Name = "formsPlot1";
this.formsPlot1.Size = new System.Drawing.Size(901, 703);
this.formsPlot1.TabIndex = 0;
this.formsPlot1.Load += new System.EventHandler(this.formsPlot1_Load);
//
// button1
//
this.button1.Location = new System.Drawing.Point(545, 753);
this.button1.Name = "button1";
this.button1.Size = new System.Drawing.Size(183, 31);
this.button1.TabIndex = 1;
this.button1.Text = "Genetic Fuzzy PID";
this.button1.UseVisualStyleBackColor = true;
this.button1.Click += new System.EventHandler(this.button1_Click);
//
// formsPlot2
//
this.formsPlot2.Location = new System.Drawing.Point(908, 47);
this.formsPlot2.Margin = new System.Windows.Forms.Padding(5, 4, 5, 4);
this.formsPlot2.Name = "formsPlot2";
this.formsPlot2.Size = new System.Drawing.Size(369, 243);
this.formsPlot2.TabIndex = 2;
//
// formsPlot3
//
this.formsPlot3.Location = new System.Drawing.Point(908, 273);
this.formsPlot3.Margin = new System.Windows.Forms.Padding(5, 4, 5, 4);
this.formsPlot3.Name = "formsPlot3";
this.formsPlot3.Size = new System.Drawing.Size(369, 241);
this.formsPlot3.TabIndex = 3;
//
// formsPlot4
//
this.formsPlot4.Location = new System.Drawing.Point(908, 522);
this.formsPlot4.Margin = new System.Windows.Forms.Padding(5, 4, 5, 4);
this.formsPlot4.Name = "formsPlot4";
this.formsPlot4.Size = new System.Drawing.Size(369, 241);
this.formsPlot4.TabIndex = 4;
//
// button2
//
this.button2.Location = new System.Drawing.Point(734, 753);
this.button2.Name = "button2";
this.button2.Size = new System.Drawing.Size(193, 31);
this.button2.TabIndex = 5;
this.button2.Text = "Fuzzy PID";
this.button2.UseVisualStyleBackColor = true;
this.button2.Click += new System.EventHandler(this.button2_Click);
//
// textBox1
//
this.textBox1.Location = new System.Drawing.Point(116, 753);
this.textBox1.Name = "textBox1";
this.textBox1.Size = new System.Drawing.Size(176, 27);
this.textBox1.TabIndex = 6;
this.textBox1.Text = "10 / 1 1 0.1";
//
// button3
//
this.button3.Location = new System.Drawing.Point(314, 753);
this.button3.Name = "button3";
this.button3.Size = new System.Drawing.Size(143, 31);
this.button3.TabIndex = 7;
this.button3.Text = "System";
this.button3.UseVisualStyleBackColor = true;
this.button3.Click += new System.EventHandler(this.button3_Click);
//
// button4
//
this.button4.Location = new System.Drawing.Point(757, 33);
this.button4.Name = "button4";
this.button4.Size = new System.Drawing.Size(143, 31);
this.button4.TabIndex = 8;
this.button4.Text = "Clear";
this.button4.UseVisualStyleBackColor = true;
this.button4.Click += new System.EventHandler(this.button4_Click);
//
// textBox2
//
this.textBox2.Location = new System.Drawing.Point(472, 755);
this.textBox2.Name = "textBox2";
this.textBox2.Size = new System.Drawing.Size(67, 27);
this.textBox2.TabIndex = 9;
this.textBox2.Text = "100";
this.textBox2.TextChanged += new System.EventHandler(this.textBox2_TextChanged);
//
// FMain
//
this.AutoScaleDimensions = new System.Drawing.SizeF(8F, 20F);
this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font;
this.ClientSize = new System.Drawing.Size(1291, 828);
this.Controls.Add(this.textBox2);
this.Controls.Add(this.button4);
this.Controls.Add(this.button3);
this.Controls.Add(this.textBox1);
this.Controls.Add(this.button2);
this.Controls.Add(this.formsPlot4);
this.Controls.Add(this.formsPlot3);
this.Controls.Add(this.formsPlot2);
this.Controls.Add(this.button1);
this.Controls.Add(this.formsPlot1);
this.Name = "FMain";
this.Text = "PID Controller with Fuzzy";
this.Load += new System.EventHandler(this.FMain_Load);
this.ResumeLayout(false);
this.PerformLayout();
}
#endregion
private ScottPlot.FormsPlot formsPlot1;
private Button button1;
private ScottPlot.FormsPlot formsPlot2;
private ScottPlot.FormsPlot formsPlot3;
private ScottPlot.FormsPlot formsPlot4;
private Button button2;
private TextBox textBox1;
private Button button3;
private Button button4;
private TextBox textBox2;
}
}

564
Esiur.Analysis.Test/FSoft.cs Normal file
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using Esiur.Analysis.DSP;
using Esiur.Analysis.Fuzzy;
using Esiur.Analysis.Optimization;
using Esiur.Analysis.Signals;
using Esiur.Analysis.Units;
using Microsoft.VisualBasic.Logging;
using ScottPlot;
using ScottPlot.Drawing.Colormaps;
using System.Security.Cryptography;
using Esiur.Analysis.Statistics;
using System.Diagnostics;
namespace Esiur.Analysis.Test
{
public partial class FSoft : Form
{
private double[] num = new double[] { 10 };
private double[] denum = new double[] { 1, 1, 0.1 };
private int interval = 3000;
private double stability = 100;
public FSoft()
{
InitializeComponent();
//var outage = Capacity.ComputeOutage(20000000, new Capacity.CSI[]
//{
// new Capacity.CSI(PowerUnit.FromDb(20), 0.1),
// new Capacity.CSI(PowerUnit.FromDb(15), 0.15),
// new Capacity.CSI(PowerUnit.FromDb(10), 0.25),
// new Capacity.CSI(PowerUnit.FromDb(5), 0.25),
// new Capacity.CSI(PowerUnit.FromDb(0), 0.15),
// new Capacity.CSI(PowerUnit.FromDb(-5), 0.1),
//});
var outage = Capacity.ComputeOutage(1, new Capacity.CSI[]
{
new Capacity.CSI(PowerUnit.FromDb(30), 0.2),
new Capacity.CSI(PowerUnit.FromDb(20), 0.3),
new Capacity.CSI(PowerUnit.FromDb(10), 0.3),
new Capacity.CSI(PowerUnit.FromDb(0), 0.2),
});
var low = new ContinuousSet(MembershipFunctions.Descending(20, 40));
var mid = new ContinuousSet(MembershipFunctions.Triangular(20, 40, 60));
var high = new ContinuousSet(MembershipFunctions.Ascending(40, 60));
var bad = new ContinuousSet(MembershipFunctions.Descending(0, 30));
var ok = new ContinuousSet(MembershipFunctions.Triangular(20, 50, 80));
var excelent = new ContinuousSet(MembershipFunctions.Ascending(70, 100));
var small = new ContinuousSet(MembershipFunctions.Descending(100, 200));
var avg = new ContinuousSet(MembershipFunctions.Triangular(100, 200, 300));
var big = new ContinuousSet(MembershipFunctions.Ascending(200, 300));
//var speedIsLowThenSmall = new FuzzyRule("Low=>Small", low, small);
double rating = 80;
for (double temp = 60; temp < 100; temp++)
{
var v = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
temp.Is(low).And(rating.Is(bad)).Then(small),
temp.Is(mid).And(rating.Is(ok)).Then(avg),
temp.Is(high).And(rating.Is(excelent)).Then(big),
}, MamdaniDefuzzifierMethod.CenterOfGravity, 100, 300, 1);
}
}
private void FMain_Load(object sender, EventArgs e)
{
//Ki -29:69 Kp -54:121 Kd 29:112
var config = new FuzzyChromosome() { KiStart = -29, KiLength = 69, KpStart = -54, KpLength = 121, KdStart = 29, KdLength = 112 };
double errStart = -0.412312, errEnd = 1, errAccStart = 0.011, errAccEnd = 0.1;
var lowErr = new ContinuousSet(MembershipFunctions.Descending(errStart, errEnd / 2.0));
var midErr = new ContinuousSet(MembershipFunctions.Triangular(errStart, errEnd / 2, errEnd));
var highErr = new ContinuousSet(MembershipFunctions.Ascending(errEnd / 2.0, errEnd));
var lowAccErr = new ContinuousSet(MembershipFunctions.Descending(errAccStart, errAccEnd / 2.0));
var midAccErr = new ContinuousSet(MembershipFunctions.Triangular(errAccStart, errAccEnd / 2.0, errAccEnd));
var highAccErr = new ContinuousSet(MembershipFunctions.Ascending(errEnd / 2.0, errAccEnd));
var kiSmall = new ContinuousSet(MembershipFunctions.Descending(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1));
var kiAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
var kiBig = new ContinuousSet(MembershipFunctions.Ascending((config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
var kdSmall = new ContinuousSet(MembershipFunctions.Descending(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1));
var kdAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
var kdBig = new ContinuousSet(MembershipFunctions.Ascending((config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
var kpSmall = new ContinuousSet(MembershipFunctions.Descending(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1));
var kpAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
var kpBig = new ContinuousSet(MembershipFunctions.Ascending((config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
var x = Enumerable.Range(0, interval).Select(x => x * 0.01).ToArray();
var step = Enumerable.Repeat(1, interval).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(num, denum, 0.01);
var motorPID = new TransferFunction(num, denum, 0.01);
var motorFuzzyPID = new TransferFunction(num, denum, 0.01);
//double Kp = 2, Ki = 0.4, Kd = 0.4;
double Ki = -1.9181372, Kp = 18.625, Kd = 0.38281253;
var pid = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var fuzzyPID = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var sysOut = new double[step.Length];
var sysOutFuzzyPID = new double[step.Length];
var sysOutPID = new double[step.Length];
var pidOut = new double[step.Length];
var pidOutFuzzy = new double[step.Length];
var errorOutPID = new double[step.Length];
var errOut = new double[step.Length];
var errAccOut = new double[step.Length];
//var errorAccOut = new double[step.Length];
var errorOutFuzzy = new double[step.Length];
var errorOutAccFuzzy = new double[step.Length];
for (var i = 0; i < step.Length; i++)
{
sysOut[i] = motor.Evaluate(step[i]);
errOut[i] = stability - sysOut[i];
errAccOut[i] = errOut[i] - (i == 0 ? 0 : errOut[i - 1]);
sysOutPID[i] = motorPID.Evaluate(step[i] + (i == 0 ? 0 : pidOut[i - 1]));
sysOutFuzzyPID[i] = motorFuzzyPID.Evaluate(step[i] + (i == 0 ? 0 : pidOutFuzzy[i - 1]));
errorOutPID[i] = (stability - sysOutPID[i]);
errorOutFuzzy[i] = (stability - sysOutFuzzyPID[i]);
errorOutAccFuzzy[i] = (errorOutFuzzy[i] - (i == 0 ? 0 : errorOutFuzzy[i - 1]));
pidOut[i] = pid.Evaluate(errorOutPID[i]);
pidOutFuzzy[i] = fuzzyPID.Evaluate(errorOutFuzzy[i]);
var ki = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
var kp = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
var kd = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
fuzzyPID.InputCoefficients[0] = ki;
fuzzyPID.InputCoefficients[1] = kp;
fuzzyPID.InputCoefficients[1] = kd;
}
Debug.WriteLine($"Error Values Min: {errOut.Min()} Max: {errOut.Max()} ");
Debug.WriteLine($"Error Acc Values Min: {errAccOut.Min()} Max: {errAccOut.Max()} ");
formsPlot1.Plot.AddScatter(x, sysOut, Color.Red);
formsPlot1.Plot.AddScatter(x, sysOutPID, Color.Blue);
formsPlot1.Plot.AddScatter(x, sysOutFuzzyPID, Color.Green);
formsPlot1.Refresh();
}
struct KK
{
public float Ki;
public float Kp;
public float Kd;
public override string ToString()
{
return $"Ki {Ki} Kp {Kp} Kd {Kd}";
}
}
struct FuzzyChromosome
{
////public sbyte KiInputErrPosition;
//public sbyte KiInputErrScale;
////public sbyte KiInputErrAccPosition;
//public sbyte KiInputErrAccScale;
////public sbyte KiOutputPosition;
//public sbyte KiOutputScale;
public sbyte KiStart;
public sbyte KiLength;
public sbyte KdStart;
public sbyte KdLength;
public sbyte KpStart;
public sbyte KpLength;
public override string ToString()
{
return $"Ki {KiStart}:{KiLength} Kp {KpStart}:{KpLength} Kd {KdStart}:{KdLength}";
}
}
private double CalculateFuzzyPIDStepError(FuzzyChromosome config, double errStart, double errEnd, double errAccStart, double errAccEnd, bool draw, string label)
{
var lowErr = new ContinuousSet(MembershipFunctions.Descending(errStart, errStart + (errEnd - errStart) * 0.5));
var midErr = new ContinuousSet(MembershipFunctions.Triangular(errStart, errStart + (errEnd - errStart) * 0.5, errEnd));
var highErr = new ContinuousSet(MembershipFunctions.Ascending(errStart + (errEnd - errStart) * 0.5, errEnd));
var lowAccErr = new ContinuousSet(MembershipFunctions.Descending(errAccStart, errAccStart + (errAccEnd - errAccStart) * 0.5));
var midAccErr = new ContinuousSet(MembershipFunctions.Triangular(errAccStart, errAccStart + (errAccEnd - errAccStart) * 0.5, errAccEnd));
var highAccErr = new ContinuousSet(MembershipFunctions.Ascending(errAccStart + (errAccEnd - errAccStart) * 0.5, errAccEnd));
var kiSmall = new ContinuousSet(MembershipFunctions.Descending(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1));
var kiAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KiStart * 0.1, (config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
var kiBig = new ContinuousSet(MembershipFunctions.Ascending((config.KiStart + (config.KiLength * 0.5)) * 0.1, (config.KiStart + config.KiLength) * 0.1));
var kdSmall = new ContinuousSet(MembershipFunctions.Descending(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1));
var kdAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KdStart * 0.1, (config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
var kdBig = new ContinuousSet(MembershipFunctions.Ascending((config.KdStart + (config.KdLength * 0.5)) * 0.1, (config.KdStart + config.KdLength) * 0.1));
var kpSmall = new ContinuousSet(MembershipFunctions.Descending(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1));
var kpAvg = new ContinuousSet(MembershipFunctions.Triangular(config.KpStart * 0.1, (config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
var kpBig = new ContinuousSet(MembershipFunctions.Ascending((config.KpStart + (config.KpLength * 0.5)) * 0.1, (config.KpStart + config.KpLength) * 0.1));
double Ki = -1.9181372, Kp = 18.625, Kd = 0.38281253;
//double Ki = 1, Kp = 1, Kd = 1;
var step = Enumerable.Repeat(1, interval).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(num, denum, 0.01);
var fuzzyPID = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
var sysOutFuzzyPID = new double[step.Length];
var pidOutFuzzy = new double[step.Length];
var errorOutFuzzy = new double[step.Length];
var errorOutAccFuzzy = new double[step.Length];
for (var i = 0; i < step.Length; i++)
{
sysOutFuzzyPID[i] = motor.Evaluate(step[i] + (i == 0 ? 0 : pidOutFuzzy[i - 1]));
errorOutFuzzy[i] = (stability - sysOutFuzzyPID[i]);
errorOutAccFuzzy[i] = (errorOutFuzzy[i] - (i == 0 ? 0 : errorOutFuzzy[i - 1]));
var ki = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kiAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kiBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kiBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
if (double.IsNaN(ki))
return double.MaxValue;
var kp = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kpAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kpBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kpBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
if (double.IsNaN(kp))
return double.MaxValue;
var kd = MamdaniDefuzzifier.Evaluate(new INumericalSet<double>[]
{
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(lowErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdSmall),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(midErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(lowAccErr)).Then(kdAvg),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(midAccErr)).Then(kdBig),
errorOutFuzzy[i].Is(highAccErr).And(errorOutAccFuzzy[i].Is(highAccErr)).Then(kdBig),
}, MamdaniDefuzzifierMethod.CenterOfGravity, -20, 20, 0.5);
if (double.IsNaN(kd))
return double.MaxValue;
fuzzyPID.InputCoefficients[0] = ki;
fuzzyPID.InputCoefficients[1] = kp;
fuzzyPID.InputCoefficients[1] = kd;
pidOutFuzzy[i] = fuzzyPID.Evaluate(errorOutFuzzy[i]);
}
if (draw)
{
formsPlot1.Plot.Clear();
var x = Enumerable.Range(0, interval).Select(x => x * 0.01).ToArray();
formsPlot1.Plot.AddScatter(x, sysOutFuzzyPID, Color.Green);
formsPlot1.Plot.AddText(label, 0, 1.5, 24, Color.DarkOrange);
formsPlot1.Refresh();
formsPlot2.Plot.Clear();
var range = FuzzyExtensions.Range(config.KiStart * 0.1, (config.KiStart + config.KiLength) * 0.1, 0.1);
formsPlot2.Plot.AddScatter(range, kiSmall.Sample(range));
formsPlot2.Plot.AddScatter(range, kiAvg.Sample(range));
formsPlot2.Plot.AddScatter(range, kiBig.Sample(range));
//formsPlot2.Plot.AddText("Ki", 0, 0, 20);
formsPlot2.Refresh();
formsPlot3.Plot.Clear();
range = FuzzyExtensions.Range(config.KpStart * 0.1, (config.KpStart + config.KpLength) * 0.1, 0.1);
formsPlot3.Plot.AddScatter(range, kpSmall.Sample(range));
formsPlot3.Plot.AddScatter(range, kpAvg.Sample(range));
formsPlot3.Plot.AddScatter(range, kpBig.Sample(range));
//formsPlot2.Plot.AddText("Kp", 0, 0, 20);
formsPlot3.Refresh();
formsPlot4.Plot.Clear();
range = FuzzyExtensions.Range(config.KdStart * 0.1, (config.KdStart + config.KdLength) * 0.1, 0.1);
formsPlot4.Plot.AddScatter(range, kdSmall.Sample(range));
formsPlot4.Plot.AddScatter(range, kdAvg.Sample(range));
formsPlot4.Plot.AddScatter(range, kdBig.Sample(range));
//formsPlot2.Plot.AddText("Kd", 0, 0, 20);
formsPlot4.Refresh();
}
//Debug.WriteLine("ERR " + errorOutFuzzy.Max() + " " + errorOutFuzzy.Min());
return errorOutFuzzy.RMS();
}
private double CalculatePIDStepError(double Kd, double Kp, double Ki, bool draw, string label)
{
var step = Enumerable.Repeat(1, interval).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(num, denum, 0.01);
var sysOutPID = new double[step.Length];
var pidOut = new double[step.Length];
var errorOutPID = new double[step.Length];
var pid = new TransferFunction(new double[] { Kd, Kp, Ki }, new double[] { 1, 1 }, 0.01);
for (var i = 0; i < step.Length; i++)
{
sysOutPID[i] = motor.Evaluate(step[i] + (i == 0 ? 0 : pidOut[i - 1]));
if (double.IsInfinity(sysOutPID[i]))
Console.WriteLine();
errorOutPID[i] = (stability - sysOutPID[i]);
if (double.IsNaN(errorOutPID[i]))
Console.WriteLine();
pidOut[i] = pid.Evaluate(errorOutPID[i]);
if (double.IsInfinity(pidOut[i]))
Console.WriteLine();
}
if (draw)
{
formsPlot1.Plot.Clear();
var x = Enumerable.Range(0, interval).Select(x => x * 0.01).ToArray();
formsPlot1.Plot.AddText(label, 0, 1.5, 24, Color.DarkOliveGreen);
formsPlot1.Plot.AddScatter(x, sysOutPID, Color.DeepSkyBlue);
formsPlot1.Refresh();
}
return errorOutPID.RMS();
}
private void button1_Click(object sender, EventArgs e)
{
var genetic = new Genetic<FuzzyChromosome>(100, k =>
{
if (float.IsNaN(k.KiStart)
|| float.IsNaN(k.KiLength)
|| float.IsNaN(k.KpStart)
|| float.IsNaN(k.KiLength)
|| float.IsNaN(k.KdStart)
|| float.IsNaN(k.KiLength))
return (double.MaxValue);
if (k.KiLength < 0 || k.KpLength < 0 || k.KdLength < 0)// k.KiStart > k.KiEnd || k.KpStart > k.KpEnd || k.KdStart > k.KdEnd)
return (double.MaxValue);
var r = CalculateFuzzyPIDStepError(k, -(stability / 2), stability / 2, -(stability / 2), stability / 2, false, null);
if (double.IsNaN(r))
Console.WriteLine();
return r;
});
foreach (var (generation, fitness, k) in genetic.Evaluate(100))
CalculateFuzzyPIDStepError(k, -(stability / 2), stability / 2, -(stability / 2), stability / 2, true, $"Fuzzy PID: Generation {generation} Fitness {fitness}\r\n{k}");
// Console.WriteLine(best);
}
private void button2_Click(object sender, EventArgs e)
{
var gen = new Genetic<KK>(100, k =>
{
if (float.IsNaN(k.Ki) || float.IsNaN(k.Kp) || float.IsNaN(k.Kd))
return (double.MaxValue);
var r = CalculatePIDStepError(k.Kd, k.Kp, k.Ki, false, null);
if (double.IsNaN(r))
Console.WriteLine();
return r;
});
foreach (var (generation, fitness, k) in gen.Evaluate(100))
CalculatePIDStepError(k.Kd, k.Kp, k.Ki, true, $"PID: Generation {generation} Fitness {fitness}\r\n {k}");
}
private void button3_Click(object sender, EventArgs e)
{
num = textBox1.Text.Split("/").First().Trim().Split(" ").Select(x=>Convert.ToDouble(x)).ToArray();
denum = textBox1.Text.Split("/").Last().Trim().Split(" ").Select(x=>Convert.ToDouble(x)).ToArray();
var x = Enumerable.Range(0, interval).Select(x => x * 0.01).ToArray();
var step = Enumerable.Repeat(1, interval).Select(x => (double)x).ToArray();
step[0] = 0;
var motor = new TransferFunction(num, denum, 0.01);
var sysOut = new double[step.Length];
var errOut = new double[step.Length];
var errAccOut = new double[step.Length];
for (var i = 0; i < step.Length; i++)
{
sysOut[i] = motor.Evaluate(step[i]);
errOut[i] = stability - sysOut[i];
errAccOut[i] = errOut[i] - (i == 0 ? 0 : errOut[i - 1]);
}
Debug.WriteLine($"Error Values Min: {errOut.Min()} Max: {errOut.Max()} ");
Debug.WriteLine($"Error Acc Values Min: {errAccOut.Min()} Max: {errAccOut.Max()} ");
formsPlot1.Plot.AddScatter(x, sysOut, Color.Red);
formsPlot1.Refresh();
}
private void button4_Click(object sender, EventArgs e)
{
formsPlot1.Plot.Clear();
formsPlot1.Refresh();
}
private void formsPlot1_Load(object sender, EventArgs e)
{
}
private void textBox2_TextChanged(object sender, EventArgs e)
{
double s;
if (double.TryParse(textBox2.Text, out s))
stability = s;
}
}
}

0
Esiur.Analysis.Test/FMain.resx → Esiur.Analysis.Test/FSoft.resx
View File

2
Esiur.Analysis.Test/Program.cs
View File

@ -11,7 +11,7 @@ namespace Esiur.Analysis.Test
// To customize application configuration such as set high DPI settings or default font,
// see https://aka.ms/applicationconfiguration.
ApplicationConfiguration.Initialize();
Application.Run(new FMain());
Application.Run(new FSoft());
}
}
}

1
Esiur.Analysis/DSP/Functions.cs
View File

@ -15,7 +15,6 @@ namespace Esiur.Analysis.DSP
return rt;
}
public static double[] Convolve(this double[] signal, double[] filter)
{
var length = signal.Length + filter.Length - 1;

8
Esiur.Analysis/Fuzzy/DiscreteSet.cs
View File

@ -66,7 +66,11 @@ namespace Esiur.Analysis.Fuzzy
{
var r = vector.Where(x => x.Key >= from && x.Key <= to).ToArray();
return r.Sum(x => x.Key * x.Value ) / r.Sum(x=>x.Value);
var total = r.Sum(x => x.Value);
if (total == 0)
return 0;
else
return r.Sum(x => x.Key * x.Value ) / total;
}
public KeyValuePair<double, double>[] Minimas
@ -78,6 +82,6 @@ namespace Esiur.Analysis.Fuzzy
}
}
public double[] ToArray() => vector.Values.ToArray();
}
}

37
Esiur.Analysis/Fuzzy/FuzzyExtensions.cs
View File

@ -41,5 +41,42 @@ namespace Esiur.Analysis.Fuzzy
return rt;
}
public static double[] Sample(this INumericalSet<double> set, double[] time)
{
var rt = new double[time.Length];
for (var i = 0; i < time.Length; i++)
rt[i] = set[time[i]];
return rt;
}
public static double[] Sample(this INumericalSet<double> set, double from, double to, double step)
{
var size = (int)((to - from) / step);
var rt = new double[size];
var s = 0;
for (var i = from; i < to && s < size; i+=step)
rt[s++] = set[i];
return rt;
}
public static double[] Range(double from, double to, double step)
{
var size = (int)((to - from) / step);
if (size == 0)
return new double[] { from };
var rt = new double[size];
var s = 0;
for (var i = from; i < to && s < size; i += step)
rt[s++] = i;
return rt;
}
}
}

4
Esiur.Analysis/Fuzzy/MembershipFunction.cs
View File

@ -23,7 +23,7 @@ namespace Esiur.Analysis.Fuzzy
{
return new MembershipFunction(x =>
{
if (x <= peak) return 1;
if (x <= peak) return 0;
if (x > peak && x < end) return (end - x) / (end - peak);
return 0;
});
@ -33,7 +33,7 @@ namespace Esiur.Analysis.Fuzzy
{
return new MembershipFunction(x =>
{
if (x >= peak) return 1;
if (x >= peak) return 0;
if (x < peak && x > start) return (x - start) / (peak - start);
return 0;
});

18
Esiur.Analysis/Optimization/Genetic.cs
View File

@ -88,23 +88,25 @@ namespace Esiur.Analysis.Optimization
}
public T Evaluate(int maxIterations)
public IEnumerable<(int, double, T)> Evaluate(int maxIterations)
{
GeneratePopultation();
var generation = 0;
T best;
KeyValuePair<T, double> best;
do
{
var ordered = GetFitness().OrderBy(x => x.Value).ToArray();
best = ordered[0].Key;
if (ordered[0].Value == 0)
best = ordered[0];
if (best.Value == 0)
break;
yield return (generation, best.Value, best.Key);
// Elitism selection ( 10% of fittest population )
var eliteCount = (int)(ordered.Length * 0.1);
@ -124,12 +126,14 @@ namespace Esiur.Analysis.Optimization
Population = newGeneration;
Debug.WriteLine($"Gen {generation} Fittest: {ordered.First().Value} {ordered.First().Key.ToString()} ");
} while (generation++ < maxIterations);
Debug.WriteLine($"Gen {generation} Best: {best.ToString()} ");
return best;
yield return (generation, best.Value, best.Key);
}
}
}