z-logo
open-access-imgOpen Access
System identification based PSO approach for networked DC servo motor
Author(s) -
Ibtihal Akram,
Osama A. Awad
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1090/1/012059
Subject(s) - particle swarm optimization , control theory (sociology) , dc motor , computer science , system identification , pid controller , control engineering , a priori and a posteriori , servomechanism , controller (irrigation) , servomotor , armature (electrical engineering) , engineering , control (management) , algorithm , artificial intelligence , electromagnetic coil , data modeling , temperature control , agronomy , philosophy , epistemology , database , electrical engineering , biology
Networked control system (NCS) suffers from inherent time delay and packet loss associated with any communication network. To build a controller that overcomes these issues, we need to know the accurate model of the system a priori. But, unfortunately most of the practical systems faced with lack in available and complete specifications of the physical system that helps in developing accurate mathematical model. This paper provides an experimentally identification method for any system based on Particle Swarm Optimization approach. The objective function to be minimized is based on the integral squared error criterion between the experimental and modeled trajectories. An armature-controlled DC motor with gearbox in lab is examined. The practical system trajectory represents the angular rotation of the output shaft. The DC motor system is modeled and controlled using fuzzy PID controller by the presented approach. Experimental results show that model equation has been successfully found with 94% accuracy. Also, a methodology for modeling the time delay in WNCS is presented.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here