Speed Control System of BLDC Motor using PI Anti – Windup Controller on an Autonomous Vehicle Prototype (AVP)

2018 ◽  
Author(s):  
Fachrur Razy Rahman ◽  
Arief Syaichu Rohman ◽  
Iyas Munawar ◽  
Sarin Sereyvatha
Keyword(s):  
Control System ◽  
Autonomous Vehicle ◽  
Speed Control ◽  
Bldc Motor ◽  
Speed Control System

scholarly journals Measurement, Modeling, and Optimization Speed Control of BLDC Motor Using Fuzzy-PSO Based Algorithm

2021 ◽  
Vol 5 (1) ◽  
pp. 17-25
Author(s):  
Izza Anshory ◽  
Dwi Hadidjaja ◽  
Indah Sulistiyowati
Keyword(s):  
Control System ◽  
Steady State ◽  
Rise Time ◽  
Speed Control ◽  
Physical Parameters ◽  
Control Methods ◽  
Bldc Motor ◽  
Motor Speed ◽  
Modeling And Optimization ◽  
Speed Control System

Measurement, modeling, and optimization are three important components that must be done to get a better system on the BLDC motor speed control system. The problem that arises in the BLDC motor speed control system is the instability indicated by a high overshoot value, a slow rise time value, and a high error steady-state. The purpose of this study is to increase the stability indicator by eliminating the high value of overshoot and error steady-state and increasing the value of the rise time. The method used in this research is to measure the input and output physical parameters, to model the BLDC motor plant mathematically and the last is to perform optimization using several control methods such as Proportional Integral Derivative (PID) control, fuzzy logic intelligent control, and Particle Swarm Optimization algorithm. (PSO). Experimental and simulation results show that the PSO algorithm has a better value in increasing stability indicators when compared to the other two control methods with a rise time of 0.00121 seconds, settling time of 0.00241 seconds, and overshoot of 0%.

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