Published February 29, 2020 | Version v1
Journal article Open

An Effective Technique for Tuning the Time Delay System with PID Controller-Ant Lion Optimizer Algorithm with ANN Technique

  • 1. Research Scholar, Dept of Electronics & Communication, Sathyabama University Chennai, India.
  • 2. Assistant Professor, Dept of Electronics & Communication, Sathyabama University Chennai, India.
  • 1. Publisher

Description

Nowadays, the PID controller is very common controller as well as very important controller in industrial utilizations. In the paper, proposed an ALO algorithm and ANN controller is utilized to enhance PID controller performance and control the tuning of TDS. TDS stands for Time delay system. ALO stands for Ant lion optimizer and ANN stands for Artificial neural network. In terms of parameters controlling, the time delay system is controlled and for different delay events low overshoot and fast time settling is reached. The novelty of the presented method is enhancing the PID controller performance by optimizing the PID gain parameters and controlling the highorder TDS. The performance of time delay system can be enhanced through decreasing error, tracking, time delay & error, rapid and exactly for their corresponding reference values. For parameter controlling of time delay system along optimal values, can be significantly enhanced the performance. To analyze the characteristics of the presented method, the various time delay systems are analyzed. The input and gain parameters were utilized to evaluate the objective function from tuning system. Based on proposed method, the optimal result is achieved and evaluated the increae time, settling time, overshoot as well as steady state error in TDS. The suggested controller is executed in MATLAB/Simulink work site and the presented technique performance examined through performance indexes and time domain specifications are evaluated using presented method compared to previous methods like ABC (Artificial Bee colony) algorithm, GSA (Gravitational Search Algorithm) ,FA (Firefly Algorithm).

Files

C5220029320.pdf

Files (507.4 kB)

Name Size Download all
md5:07195cd188e1a19d4258b8b99ebcef3c
507.4 kB Preview Download

Additional details

Related works

Is cited by
Journal article: 2249-8958 (ISSN)

Subjects

ISSN
2249-8958
Retrieval Number
C5220029320/2020©BEIESP