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520 Motor📖
1.About motor
  • About motor
2.ROS robot control board drive
  • 2.1 Control motor
  • 2.2 Timer captures encoder data
  • 2.3 PID control robot car
  • 2.4 Kinematic Analysis-Mecanum wheel structure
  • 2.5 Kinematic Analysis-Ackerman structure
  • 2.6 Kinematic Analysis-4WD structure
3.STM32 Self-balancing car tutorials
Get started quickly
  • 03.P, PI, PD controller theory
  • 01.Balancing car assembly
  • 02.Get started quicklyy
  • 03.Balance car interface description
  • 04.Common Problem Analysis
  • 05.Balance Car V2 Library Function Development Manual
Environment construction and development
  • 01.MDK-ARM installation
  • 02.STM32CubeIDE installation
  • 03.Common driver installation
  • 04.Download the program
  • 05.MDK-ARM project usage
  • 06.Program simulation
Robot car PID control course
  • 01.PID basic concept
  • 02.PID example analysis
  • 04.Position PID
  • 05.Incremental PID
  • 06.Cascade PID
  • 07.Balance principle of car
  • 08.Car upright control (PD)
  • 09.Car speed ​​control (PI)
  • 10.Car steering control (PD)
  • 11.Got angle and angular velocity (DMP algorithm)
  • 12.Got angle and angular velocity (Kalman filter algorithm)
  • 13.Got angle and angular velocity(Complementary filter algorithm)
Robot car basic course
  • 01.Car parameter adjustment
  • 02.Ultrasonic obstacle avoidance
  • 03.Ultrasonic follow
  • 04.Bluetooth remote control
  • 05.Load balance
Robot car LQR control
  • Robot car LQR control
Circuit design
  • 01.Overall circuit design
  • 02.STM32 minimum system
  • 03.Serial port circuit design
  • 04.Power circuit design
  • 05.MPU6050 Circuit Design
  • 06.Motor drive circuit design
Mathematical model
  • Balance car mathematical model
4.4-channel motor drive module
Introduction and Debug
  • 1.Introduction to 4-channel motor drive board
  • 2.Control command
  • 3.Motor introduction and usage
  • 4.PC host
IIC communication
  • For Arduino
  • For ESP32
  • For Jetson NANO
  • For MSPM0G3507
  • For MSPM0G3519new
  • For PICO2
  • For RDK X5
  • For RPi5
  • For STM32
USART communication
  • For Arduino
  • For ESP32
  • For Jetson NANO
  • For MSPM0G3507
  • For MSPM0G3519new
  • For PICO2
  • For RDK X5
  • For RPi5
  • For STM32
5.2-channel motor drive module
For MSPM0G3507
  • 1.AT8236 drive tutorials
  • 2.TB6612 drive tutorials
For MSPM0G3519
  • 1.AT8236 drive tutorialsnew
  • 2.TB6612 drive tutorialsnew
Download
  • Model File
  • Annex_ROS_robot_board
  • Annex_STM32_balancing_car
  • Annex_4channel_motor_drive
  • Annex_2channel_motor_drive
Download ZIP

Welcome to 520 Motor repository

01.PID basic concept

PID basic concept

PID basic conceptRelated termsProportional (P)Integral (I)Differential (D)

PID is the acronym for Proportional, Integral, and Differential controllers, and is a commonly used closed-loop control algorithm.

PID controllers calculate the output control signal based on the current error value of the system, including proportional, integral, and differential terms, so that the system output is stable near the set value

PID

PID formula

u(t)=Kpe(t)+Ki∫t0e(t)dt+Kdde(t)2
  • Kp: Proportional gain, used to adjust the response speed and stability of the feedback control system. Increasing Kp can speed up the response speed of the system, but may cause system oscillation or overshoot; reducing Kp may cause the system to respond too slowly.

  • Ki: Integral gain, used to eliminate the steady-state error of the system. Increasing Ki can reduce the steady-state error of the system, but may cause over-regulation or oscillation of the system; reducing Ki may cause the system to be unable to eliminate the steady-state error.

  • Kd: differential gain, used to suppress the oscillation and overshoot of the system. Increasing Kd can reduce the overshoot and oscillation of the system, but may make the system more sensitive to noise and interference; reducing Kd may cause the system to respond too slowly.

  • e(t): error signal, which is the deviation between the expected value and the actual value.

Related terms

Feedback: The system output signal is again part of the input signal.

Open loop: The system output is not monitored and adjusted by the system state, and the system directly generates output based on the input signal.

Closed loop: The system monitors the system output signal and compares it with the reference signal, and then adjusts the system state to make the output close to the reference value.

Set value: The set value of the PID regulator is the value that people expect the controlled variable to reach.

Input deviation: The difference between the controlled variable and the set value.

Dynamic deviation: During the adjustment process, the deviation between the controlled quantity and the set value changes at any time. The deviation between the two at any time is called dynamic deviation.

Callback: The adjustment effect of the regulator is displayed, which makes the controlled quantity start to change from rising to falling, or from falling to rising trend, which is called callback.

Proportional (P)

Integral operation of input deviation: directly proportional to the current error, which can quickly respond to the change of error, but it is easy to cause system oscillation.

Integral (I)

Integral operation of input deviation: accumulating past errors helps to eliminate static errors, but may cause slow system response or oscillation.

Differential (D)

Differential operation of input deviation: predicting the trend of error change helps to reduce the dynamic error and oscillation of the system.

Program simulation
PID example analysis

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