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PID Speed Controller for DC Motor

PID Speed Controller for DC Motor © GPL3+

[@version 1 ] PID loop is used in this project to control the speed of a permanent magnet DC motor.

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Components and supplies

A000066 iso both
Arduino UNO & Genuino UNO
×1
Power supply 300w - 24/12 v
×1
Dc motor 24v/150w
×1
Encoder 600ppr incremental
×1
Gt2 closed loop belt
×1
INA219 I2C POWER MONITOR SENSOR
×1
Cooling fan
×2
Bluetooth hc-05
×1
LCD
×1
SERIAL I2C TO LCD
×1
Gt2 pulley 20 teeth 5mm
×1
Gt2 pulley 20 teeth 8mm
×1
On –off switch
×2
Bread board 830 tie
×1
wire
×1
IRF540 Power MOSFET
×1
Push button
×1
Voltage regulator 5v
×1
Voltage regulator 9v
×1

Necessary tools and machines

digital multimeter
3drag
3D Printer (generic)
cnc machine

Apps and online services

About this project

History of cruise control

The Blind Man Who Invented Cruise Control.

Cruise control system is a fabulous invention that helps us avoid speeding tickets and gives our feet a break on long drives. In spite of the fact that almost all drivers have used cruise control at some point, only a few drivers know much about the features origins or about the man who invented it. Ralph Teetor invented the cruise system for modern motor vehicles… and he was blind.
As early as the late 1700s, engineers began using cruise control-type technology to regulate steam engines. Ralph Teetor was personally inspired to make cruise control for cars after a few too many frustrating drives with his lawyer, who had a nasty habit of speeding up and slowing down too often. He developed cruise control in the 1940s and patented it in the early Nineteen Fifties.

Some advantages of cruise control :

  • · It's useful for long drives.
  • · Some drivers use it to avoid subconsciously violating speed limits.
  • · Increased fuel efficiency.

Abstract

The purpose of this project is to have a simplest speed control unit done by digital controller and here we used Arduino Uno development board to apply a basic control theory to the system. PID loop is used in this project to control the speed of DC motor. And we also included different controller types to control the speed of DC motor. GUI is made for setting the required speed and serial plotter & monitor for better visualization the data form the motor.

Aim and Objectives

The aim of the project includes for several reasons:

  • Control the speed of motor by applying different controller types (pid, pi, p, i) and learn the difference between them.
  • For more understanding the control theory and tuning methods.

Skills and knowledge

  • Autocad skills ( 2D & 3D parts )
  • Arduino c programming ( program arduino uno )
  • Matlab & Simulink ( T.f & parameter estimation & tuning PID )
  • C# programming ( build GUI )

Algorithms

  • kalman filter algorithm ( filter the speed sensor from noise)
  • Non-linearleast squares algorithm ( parameter estimation)

DC Motor Speed Control

The physical parameters for the DC motor “MY6812” are: ( from parameter estimation)

  • (J) moment of inertia of therotor 1.2130e-05 kg.m^2
  • (b) motor viscous frictionconstant 1.5319e-04 N.m.s
  • (Ke) electromotive forceconstant 0.0034 V/rad/sec
  • (Kt) motor torque constant 0.0034 N.m/Amp
  • (R) electric resistance 0.0710 Ohm
  • (L) electric inductance 0.0127 H

1.Transfer Function.

2.State-Space.

the armature voltage is treated as the input and the rotational speed is chosen as the output.

3.Simulink Modeling.

4.PID control.

The speed of the dc motor can be controlled using a different controller. In this project,speed is controlled by the PID controller.

A PID controller produces an output signal consisting of three terms- one proportional to error signal, another one proportional to integral of error signal and third one proportional to the derivative of the error signal.

  • The proportional controller stabilizes the gain but produces a steady state error.
  • The integral controller reduces or eliminates the steady state error.
  • The derivative controller reduces the rate of change of error.

PIDcontrollers have higher stability , no offset and reduced overshoot .

5.Tuning PID

There are many different ways to tune PID control of any system like ZIEGLER NICHOLS methods or even TRY AND ERROR method to get the required performance.

In this section, PID tuner toolbox is used to tune PID depends on response time [slower– faster] and the transient behavior [aggressive – robust] that you give.

6.Parameters Estimation.

Parameter estimation plays a criticalrole in accurately describing system behavior through mathematical models suchas statistical probability distribution functions, parametric dynamic models.

Common tasks for parameter estimation:

  • Importing and analysis input-output data, like the applied voltage as input and rotor speed as the output of a DC motor.
  • Determine which model parameters and initial conditions to estimate, such as motor inductance and friction, and other parameters.

Non-linearleast squares method is used to estimate the unknown parameters.

It compares between two data:

  • measured data
  • simulation data.

Measured data comes from real system while simulation data comes from mathematical model with initial assumption as shown below :

J=0.01;

B=0.1;

K=0.01;

R=1;

L=0.5;

And after a number of iteration, the simulation data try to follow the measured data by changing these parameters to match measured data and give us realistic model result.

GUI

For displaying results by PC a GUI is designed by a c sharp windows form application using visual studio2015 text editor. by the designed GUI the power, voltage, current draws by the motor will be displayed in this application. Also, the desired speed and the value of speed sensor & error & output PWM will be shown.

Control Unit Panel.

  • · Setpoint : desired speed that user need.
  • · Sampletime : default 20 milli seconds.
  • · Disturbance: [0 -500 ], effect the value of speed sensor.
  • · Setmode : either “auto” or “manual”, where “manual” turn off the PID algorithm.
  • · Open loop configuration : activate open loop instead of closed loop [0 – 255], where “0” turn off the motor while “255” max speed can handle.
  • · Controltype : “PID”, “PI “, “P”, “I “.

Open the connect button for making a connection between ARDUINO and the PC.

  • · Com ports: choose what available.
  • · Baud rate: 9600

Then press open button from port control panel.

The GUI have also both serial monitor and serial plotter for better visualization data incoming from ARDUINO.

For serial monitor, you can copy the data and analysis it by either Microsoft excel or Matlab.

you can also save the data as txt or csv.

Difficulties And Challenges.

  • 1.How to filter the reading of speed sensor: Using kalman filter algorithm, Excellent filtering but it delay the signal a little bit.
  • 2.How to estimate the parameters of the motor: Using non-linear least squares method.Good estimate but it have some error.
  • 3.How to send and receive command from a computer :Make a GUI using c sharp windows form application.
  • 4.How to build mathematical model of the motor:Using Simulink and create subsystem.
  • 5.How to tune PID control: Using system identification toolbox from Matlab Very good result.

Design

Schematic Diagram.

Applications of PID controller.

  • Cruise control system in cars.
  • to regulate flow, temperature, pressure, level, etc.

Features And Improvements.

you can improve the system by doing the following : [@version2]

  • · Implement PID loop on faster microcontroller.
  • · Instead of using Bluetooth to make a connection between the interface and Arduino, a Wi-Fi model is better to change the speed and monitor the system from any place of the world.
  • · Add features that make the application automatically calculate the rise time and overshoot also settling time.
  • · Auto tuning option.

Videos

part1 : hardware.
part 2: GUI to control the system.

Project Time Plan.

  • · Total days working : almost 120 days.
  • · Total month working : 120 / 30 = 4 month .
  • · Almost[2-6] hours per day.

Main Parts Descriptions

Power Supply.

Power supply is needed for powering ARDUINO UNO and for motor.

  • Power = 300 watt .
  • DC output = 12 volt - 5A .
  • DC output = 24 volt - 10A.

Arduino Uno.

Either arduino uno or any digital controller to implement PID loop and for control the speed of motor and sending or receiving data by serial communication Bluetooth.

  • · Microcontroller board based on the ATmega328P.
  • · It has 14 digital input/output pins.
  • · 6 analog inputs.
  • · 16 MHz.
  • · Arduino C/C++ .

Encoder600ppr Incremental.

A rotary encoder is used to measure the rotational speed, Angle and acceleration of the object and the length measurement. Suitable for intelligent control of various displacement measurement.

  • · 600 pulses per revolution ( 600 ppr).
  • · Power= 5 -24 volt DC .
  • · Output = 2 phase [A & B] output rectangular .
  • · Maximum mechanical speed: 5000 R / min .

2D part& 3D part .

2Dpart is done by CNC machine for enclosure box to safety operation and not get hurt from power source AC Current. while 3D part is done by 3D printer for holder bracket of the DC motor and encoder speed sensor.

  • · Software design : AutoCAD.
  • · 2D part final product : CNC machine .
  • · 3D part final product : 3D printer .

DC Motor.

MY6812 24V /150W high speed brush motor is used in this project. It Popular as a scooter motor or general application motor.Extremely durable and reliable.

  • · Power output = 24V/150W.
  • · Current without load : < 0.9 A .
  • · Rated current ( with full load ) : < 8.5A .
  • · Max speed (rpm) : 3500 +/- 5 %.
  • · Rated speed (rpm) : 2500 +/- 5 %.
  • · Rated torque : 0.56 Nm .
  • · Shaft diameter : 8 mm .
  • . Efficiency : > 68%.

Mechanical Parts .

Consist of two GT2 pulley[pitch =2mm ] and a closed loop belt .

  • · GT2 pulley 20 teeth 5mm bore 6mm wide.
  • · GT2 pulley 20 teeth 8mm bore 6mm wide.
  • · Gt2 closed loop belt 400mm length 6mm wide .

LCD with I2C.

LCD 16X2 with I-squared-C synchronous communication is used in this project to display the values of set point & actual speed& error & PWM output.

With I2C device you can control the LCD with only 2 pin from any microcontroller. they are the SCL (serial clock pin ) & SDA (serial data pin) .

On arduino uno :

  • A4 (SDA) .
  • A5(SCL).
  • · LCD (Liquid Crystal Display).
  • · Power = 5v .
  • · They are good for displaying information like sensors data.
  • · They are very cheap.

Motor Driver.

A motor driver is a circuit which is usually used to control motors in autonomous robots. Motor driver act as an interface between Arduino uno microcontroller and the motor.

  • · IRF540 Power MOSFET .
  • · 10 k ohm pull-down resistor from gate to source .
  • · 1N5408 freewheeling diodes.

Bluetooth HC-05 .

This module is used to communicate between Arduino uno and any device with Bluetooth functionality like a Phone or Laptop .

  • · Operating Voltage: +5V .
  • · Range: < 100m.

INA219 Power Monitor Sensor.

To measure the current draw of the DC motor and also to measure the voltage bus & power.

  • · This module can be sensed bus voltage range 0 V to 26V.
  • · 12-bit resolution.
  • · Measure high side voltage and DC current draw.

Conclusions.

The goal was to design, build, and program a speed control unit to be used for testing the theory behind control system . and these are the advantages :

  • · Learn about the control theory and the controller tuning methods.
  • · Learn how to design a GUI that communicate with Arduino and how to send data to-from Arduino by serial communication.
  • · Learn about different methods of filtering a signal that content a noise with it like Kalman filter algorithm.
  • · Learn about the basic idea of cruising car system.
  • · Have the opportunity to learn a number of different software like Arduino ide, c sharp, AutoCAD 2d&3d, excel, Matlab &Simulink, etc.

Code

final codeArduino
//when covert string into float u will get only 2 digit after float point (.) and for
// that we cant send the value of tuning serially (kp ,ki ,kd) .
// change these value here in arduino sketch .

/* cruise control project .
 * 1)encoder 600ppr 5v two channel A,B
 * 2)motor 24v/150w max speed 3600rpm 
 * 3)motor driver control by pwm .
 * 4)arduino uno .
 * 5)power supply (12v/5a) ... (24v/10a) .
 * 6)gt2 pulley 8mm bore.
 * 7)gt2 pulley 6mm bore .
 * 8)tooth belt 400mm length 6mm width .
 * 9)(x2) fan 5v .
 * 10)(x2)led.
 * 11)(x2)switch on-off 
 * 12)bluetooth module.
 * 13)lcd+i2c .
 * 14)push button .
 * 15) others .
 */
#include <Wire.h> 
#include <LiquidCrystal_I2C.h>
#include <PID_v1.h> 
#include <FreqMeasure.h>
#include <Adafruit_INA219.h>

Adafruit_INA219 ina219;

LiquidCrystal_I2C lcd(0x27, 16, 2);

// kalman filter
double K =0;                // kalman gain 
const double R=0.5 ;      // error in measurement

double Eest=0;              // error estimate 
double pre_Eest=0;          // error estimate(t-1)

double est =0;              // estimate 
double pre_est=0;           // estimate(t-1)

double sensor_meg=0;        // from analog pin 

double p1=1; 
const double Q=0.01;     //0.01;          //1e-04;       //1e-04;    // process noise [0.001 slow response]//0.01
/////////////////////////////////////////////////
// kalman filter
 
double K8 =0;                // kalman gain 
const double R8=0.5 ;      // error in measurement [data sheet of lm35 error =0.5]

double Eest8=0;              // error estimate 
double pre_Eest8=0;          // error estimate(t-1)

double est8 =0;              // estimate 
double pre_est8=0;           // estimate(t-1)

double sensor_meg8=0;        // from analog pin 

double p18=1; 
const double Q8=0.0001;       // process noise [0.001 slow response]

// for measure f:-
float rps,rpm ;
int const ppr=600; //pulse per rev.
String data;
String receive;
int sampletime=20;
int mode;
float freq_a;
int Disturbance=0;
int controller=1;
int open_loop_pwm=86;
// sensor :-
double voltage_sensor=12;
double current_sensor=0.55;
double power_sensor=25;

// motor driver :-
int in_A=6; //PWM
//int in_B=5; //PWM
int pwm =50;


// pid parameters:-
double Setpoint,Input,Output;

// from pid matlab tune :-
//double Kp=0.00548333297173391;
//double Ki=0.0423023548974992;
//double Kd=0.000177690701568258;

double Kp=0.00206812507453938;
double Ki=0.0339782106923304; 
double Kd=3.14697363162208e-05;

// define object :-
PID myPID(&Input,&Output,&Setpoint,Kp,Ki,Kd,DIRECT);

// to apps 
String send_to(double s,double i, double e,double o,double ff,double kalman,double v_s,double c_s,double p_s){
String d = (String)s+";"
          +(String)i+";"
          +(String)e+";"
          +(String)o+";"
          +(String)ff+";"
          +(String)kalman+";"
          +(String)v_s+";"
          +(String)c_s+";"
          +(String)p_s
          ;
return d;
d="";
}

void setup() {
  lcd.begin();
  lcd.print("cruise sys");
  delay(2000);
  lcd.clear();
  pinMode(in_A,OUTPUT);
  //pinMode(in_B,OUTPUT);
  pinMode(8,INPUT_PULLUP); // must pull up to 5v to work .
  Serial.begin(9600);
  FreqMeasure.begin();
  myPID.SetMode(AUTOMATIC); //start calculation.
  myPID.SetOutputLimits(0,255);
  myPID.SetSampleTime(sampletime);
  //myPID.SetSampleTime(20); // matlab. 
  Setpoint=2000; // 12v =1800 almost.
  /////////////////////////////////////////////////////////////////////////////////
    uint32_t currentFrequency;
  // Initialize the INA219.
  // By default the initialization will use the largest range (32V, 2A).  However
  // you can call a setCalibration function to change this range (see comments).
  ina219.begin();
  // To use a slightly lower 32V, 1A range (higher precision on amps):
  //ina219.setCalibration_32V_1A();
  // Or to use a lower 16V, 400mA range (higher precision on volts and amps):
  //ina219.setCalibration_16V_400mA();

}

void right_move(){
  analogWrite(in_A,pwm);
  //digitalWrite(in_B,LOW); 
}

float get_speed(){
      if(FreqMeasure.available()) {
       // if there is data coming do something : 
      float f = FreqMeasure.countToFrequency(FreqMeasure.read());
      freq_a=f;
      
      //convert F to rps :
      rps=f/ppr;
      //convert rps to rpm :
      rpm=rps*60;
      // condition limit :
      if(rpm<0){rpm=0; }
      if(rpm>3600){rpm=3600; }
      
      // effect of disturbance :
      if(rpm>=500){
      rpm=rpm-Disturbance ;
      }
      return rpm;
      }
}

void display_lcd(){
lcd.setCursor(0,0);
lcd.print("S:");
lcd.setCursor(8,0);
lcd.print("I:");
lcd.setCursor(0,1);
lcd.print("E:");
lcd.setCursor(8,1);
lcd.print("o:");

lcd_clear();

// print to lcd after clear :
lcd.setCursor(2,0);
lcd.print((int)Setpoint);
lcd.setCursor(10,0);
lcd.print((int)Input);
lcd.setCursor(2,1);
int e=Setpoint-Input;
lcd.print((int)e);
lcd.setCursor(10,1);
lcd.print((int)Output);
// must have delay above 300ms.

}
void lcd_clear(){

for(int i=2;i<8;i++){ 
  lcd.setCursor(i,0); 
  lcd.print(" "); 
  lcd.setCursor(i,1); 
  lcd.print(" ");
}
for(int i=10;i<16;i++){ 
  lcd.setCursor(i,0); 
  lcd.print(" "); 
  lcd.setCursor(i,1); 
  lcd.print(" "); 
}

}

void parsing (String q){
  String a; // sp
  String b; // sample time
  String c; // mode operation
  String d; // disturbance 

  String a1;
  String b1;
  a=q.substring(0,q.indexOf(";"));
  b=q.substring(q.indexOf(";")+1 , q.indexOf(","));
  c=q.substring(q.indexOf(",")+1 , q.indexOf("&") );
  d=q.substring(q.indexOf("&")+1 , q.indexOf("@") );
  //
  a1=q.substring(q.indexOf("@")+1 , q.indexOf("%") );
  b1=q.substring(q.indexOf("%")+1);

controller=a1.toInt();
typeOfControl(controller);

open_loop_pwm= b1.toInt();

 Disturbance=d.toInt();
 //Output=Output-Disturbance;
 
 Setpoint=a.toInt();
 
 sampletime=b.toInt();
 myPID.SetSampleTime(sampletime);
 
 mode=c.toInt();
 if(mode==1){
  myPID.SetMode(AUTOMATIC);
 }
 else if (mode==0){
  myPID.SetMode(MANUAL);
  Output=open_loop_pwm;
 }

}

void typeOfControl(int x)
{
 
if (x==1){ // pid 
Kp=0.00548333297173391;
Ki=0.0423023548974992; 
Kd=0.000177690701568258;    
  }
  
else if (x==2){ //pi
Kp=0.00284752617249473;
Ki=0.035555779556629; 
Kd=0;    
  }
  
else if (x==3){ //p
Kp=0.0280057653779624;
Ki=0; 
Kd=0;    
  }
  
else if (x==4){ // i
Kp=0;
Ki=0.0187518091153096; 
Kd=0;    
  }
  
else if (x==5){ // oscillator
Kp=0.16;
Ki=0; 
Kd=0;   
  } 
  
myPID.SetTunings(Kp,Ki,Kd);
  
}

void loop()
{ 
unsigned long real_ms=millis();//calculate real time ms ;
// do it later not now.
 
if(Serial.available()>0){
  receive = Serial.readString();
  parsing (receive);

 }
 
right_move();
Input=get_speed();

sensor_meg=Input;
pre_Eest=p1+Q;
K=Eest/(Eest+R);
est=pre_est+K*(sensor_meg-pre_est);
Eest=(1-K)*pre_Eest;

//update kalman
pre_est=est;
p1=Eest;
Input=est;


myPID.Compute();
//Output=Output-Disturbance;
pwm=Output;

//data to serial plotter
/*
Serial.print(Setpoint);
Serial.print(" ");
Serial.print(Input);
Serial.print(" ");
Serial.println(Setpoint-Input);
*/

//show result into lcd screen
display_lcd();

// current 
  float shuntvoltage = 0;
  float busvoltage = 0;
  float current_mA = 0;
  float loadvoltage = 0;
  float power_mW = 0;

  shuntvoltage = ina219.getShuntVoltage_mV();
  busvoltage = ina219.getBusVoltage_V();
  current_mA = ina219.getCurrent_mA();
  power_mW = ina219.getPower_mW();
  loadvoltage = busvoltage + (shuntvoltage / 1000);

//
sensor_meg8=current_mA;

pre_Eest8=p18+Q8;
//
K8=Eest8/(Eest8+R8);
est8=pre_est8+K8*(sensor_meg8-pre_est8);
Eest8=(1-K8)*pre_Eest8;

//update
pre_est8=est8;
p18=Eest8;

float power_cons=busvoltage*est8;
power_cons=power_cons/1000;

// noise measurement of current sensor :
 float noise =abs( est8 - current_mA );

// send data to c#:
data=send_to(Setpoint,Input,Setpoint-Input,Output,freq_a,noise,busvoltage,est8,power_cons);
Serial.println(data); //println == as string

}
step input responseArduino
just apply 24v to the motor terminal and copy the result that appears in the serial monitor of Arduino ide.
this is for parameter estimation of the transfer function.
// this is a step input response of the dc motor.
// we need frequency and time for parameter estimation.


#include <FreqMeasure.h>

void setup() {
  Serial.begin(57600); // for faster data transmission 
  FreqMeasure.begin(); 
}

void loop() {
  if (FreqMeasure.available()) {
      float frequency = FreqMeasure.countToFrequency(FreqMeasure.read());
      Serial.print(frequency); // measure the frequency
      Serial.print("\n");
      Serial.println(micros()); // measure the time in microseconds

    }
  }
step input dataMATLAB
this is a step input data from arduino after applied 24v to the motor.
step1: convert freqency to rps then to rpm.
step2:convert time from us to s.
step3: time start from zero.
clc;
close all;

data=[
0.07	14866316
418.84	14868832
861.05	14869992
1129.94	14870936
1340.48	14871824
1546.64	14872728
1671.54	14873988
1825.03	14877048
1938.22	14880108
2059.73	14883168
2175.98	14886228
2287.35	14889288
2403.48	14892348
2503.91	14895408
2605.01	14898468
2723.87	14901532
2818.89	14904588
2955.85	14907656
3093.58	14910708
3668.04	14913768
4371.58	14916828
5251.07	14919888
6012.78	14922948
7098.49	14926012
7707.13	14929068
8681.50	14932128
9302.33	14935196
10575.02	14938428
11469.53	14941648
12509.77	14944880
12851.41	14948108
12618.30	14951344
14939.31	14954568
15223.60	14957808
15794.67	14961036
16597.51	14964260
17486.34	14967488
18823.53	14970720
18120.05	14973948
18890.20	14977188
19536.02	14980416
19925.28	14983648
20565.55	14986876
21447.72	14990100
21947.87	14993336
21739.13	14996568
22068.97	14999796
23809.52	15003020
24279.21	15006256
24242.42	15009488
23845.01	15012708
25723.47	15015952
26058.63	15019168
26490.07	15022400
26143.79	15025628
26711.19	15028860
27874.57	15032096
27972.03	15035320
27491.41	15038556
28318.58	15041780
28520.50	15045016
28520.50	15048248
28828.83	15051468
29197.08	15054708
30018.76	15057936
29357.80	15061168
29574.86	15064388
30828.52	15067624
30188.68	15070856
30769.23	15074088
30828.52	15077316
31067.96	15080540
31558.19	15083768
32128.51	15087008
31683.17	15090228
31683.17	15093460
32388.66	15096688
32323.23	15099924
32719.84	15103156
32989.69	15106388
32921.81	15109616
32653.06	15112848
33542.98	15116076
33333.33	15119308
33970.28	15122536
33264.03	15125768
33542.98	15128996
33333.33	15132220
33898.30	15135456
34261.24	15138688
34632.03	15141916
33472.80	15145140
34408.60	15148376
34334.76	15151600
34334.76	15154836
34482.76	15158060
34782.61	15161296
35010.94	15164520
34334.76	15167756
34261.24	15170988
34482.76	15174216
34632.03	15177440
34707.16	15180676
34482.76	15183912
35714.28	15187136
36117.38	15190360
36866.36	15193596
35164.83	15196820
35555.55	15200048
34934.50	15203288
35476.72	15206508
35164.83	15209748
36697.25	15212976
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36866.36	22858380
36199.09	22861616
35955.05	22864848
37037.03	22868076
36951.50	22871304
36446.47	22874528
36117.38	22877768
37209.30	22880996
36529.68	22884228
36446.47	22887452
35955.05	22890680
36866.36	22893916
36199.09	22897148
36697.25	22900376
36613.27	22903600
35794.18	22906828
37209.30	22910060
36117.38	22913296
37122.97	22916528
36781.61	22919748
37383.17	22922988
36281.18	22926212
36446.47	22929448
37383.17	22932676
37037.03	22935904
36781.61	22939136
36697.25	22942360
35476.72	22945596
36613.27	22948828
36446.47	22952056
36951.50	22955288
36529.68	22958516
36036.03	22961740
36036.03	22964972
37122.97	22968200
37037.03	22971436
35320.09	22974660
36446.47	22977896
36781.61	22981128
36613.27	22984356
37383.17	22987584
36529.68	22990808
37647.06	22994048
36529.68	22997268
36866.36	23000508
37296.04	23003732
36866.36	23006960
36697.25	23010196
37122.97	23013428
37558.68	23016652
37647.06	23019888
36117.38	23023108
36613.27	23026348
36446.47	23029576
36697.25	23032804
36613.27	23036036
36199.09	23039260
37558.68	23042496
37037.03	23045728
36866.36	23048956
36446.47	23052188
36446.47	23055416
37296.04	23058648
36697.25	23061876
36281.18	23065104
36281.18	23068336
36866.36	23071568
37209.30	23074796
35874.44	23078028
36697.25	23081252
36951.50	23084480
36866.36	23087716
36951.50	23090948
36446.47	23094176
36866.36	23097408
36951.50	23100636
37122.97	23103860
36951.50	23107096
36446.47	23110328
37383.17	23113556
36781.61	23116780
37209.30	23120016
36781.61	23123248
36697.25	23126476
36866.36	23129708
37122.97	23132936
37209.30	23136168
36529.68	23139388
36613.27	23142624
37037.03	23145856
37383.17	23149084
37122.97	23152308
36281.18	23155540
36613.27	23158776
37122.97	23162008
37037.03	23165236
36697.25	23168468
35874.44	23171696
36446.47	23174928
36697.25	23178156
36866.36	23181388
36363.64	23184616
36199.09	23187848
36363.64	23191072
36951.50	23194300
36446.47	23197536
36529.68	23200772
36446.47	23203988
36117.38	23207228
36697.25	23210456
36781.61	23213684
36613.27	23216908
36697.25	23220148
36281.18	23223368
37037.03	23226600
36781.61	23229828
37209.30	23233068
];

% convert freqency to rps 
data(:,1)=data(:,1)./600;
rps=data(:,1);

%convert time from us to s 
data(:,2)=data(:,2)./1e6;
time=data(:,2);

%rpm 
rpm=rps(:,1).*60;

% time start from zero 
time=time-min(time);
newdata=[time,rpm];

plot(time,rpm);
results of parameters estimation.Markdown
this is estimation values of our dc motor after applied nonlinear least square method from matlab.
from estimation of parameter of dc motor : 

B=1.5319e-04;
J=1.2130e-05;
K=0.0034;
L=0.0127;
R=0.0710;
all librariesMarkdown
all libraries you need to import it.
#include <Wire.h> 
#include <LiquidCrystal_I2C.h>
#include <PID_v1.h> 
#include <FreqMeasure.h>
#include <Adafruit_INA219.h>
#include <FreqMeasure.h>

Custom parts and enclosures

motor base
encoder base
2D enclosure box
Acrylic 5mm thick
cnc_rJ5tc3jHlU.dwg

Schematics

Circuit diagram
projectpidcontrol_s5LfJyZBVx.fzz
Image of Circuit diagram
Circuit ptbaosbhdr

Comments

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