JOURNAL ARTICLE

Comparison of Inverted Pendulum Control System using Proportional – Integral – Derivative (PID) and Proportional – Integral (PI)

Abstract

Inverted pendulum is a system that works to control the balance of a tool with a mass point above the pivot point, is non-linear, has many variables, and erratic. It has a less controllable configuration or the number of control inputs is less than the number of degree of freedom that can be controlled. One of posssible solutions to solve this problem is by using PID or Proportional - Integral - Derivative. PID is often used as a comparison with other control systems such as Fuzzy, Linear Quadratic Regulator (LQR) or Neural Network but there are a few researches on the control system between PID (P with PID, PI with PD, PID with PI) on Inverted Pendulum. This research seeks optimum PID parameters that correspond to the way the Inverted Pendulum works. Then, the work of the PID control system is compared with the PI control system against the results of the rotary encoder in angular form and PWM (Pulse Width Modulation) value for the motor to find which control system is best suited for the device used in this research. The results of this study show the optimum PID parameter is as follows: Kp = 9.95, Ki = 8.10, Kd = 8.10 as well as the optimum PI parameters are Kp = 8.15 and Ki = 11.55. The results of the encoders and PWM from both control systems showed that the control system of PID is more capable of achieving and maintaining the pendulum balance using an average PWM of 98.47 compared to the PI control system.

Keywords:
PID controller Control theory (sociology) Inverted pendulum Control system Pi Pulse-width modulation Mathematics Computer science Physics Temperature control Engineering Control engineering Control (management) Nonlinear system Voltage

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0.58
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Citation History

Topics

Engineering and Technology Innovations
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Industrial Automation and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Sensorless Control of Electric Motors
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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