Adaptive PID controller based on Lyapunov function neural network for time delay temperature control

Muhammad Saleheen Aftab, Muhammad Shafiq

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Temperature is an important control variable in industrial processes. In this paper, an adaptive PID control algorithm has been discussed to track the process temperature. The presented control algorithm employs Lyapunov function based artificial neural networks for online tuning of proportional, integral and derivative actions. This algorithm has been successfully tested on the laboratory temperature control process trainer. For comparative analysis, the results have been contrasted with the conventional PID scheme. The experimental findings show that improved and stable tracking is achieved with the proposed adaptive PID controller.

Original languageEnglish
Title of host publication2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479984220
DOIs
Publication statusPublished - Mar 12 2015
Event2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015 - Muscat, Oman
Duration: Feb 1 2015Feb 4 2015

Publication series

Name2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

Other

Other2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015
Country/TerritoryOman
CityMuscat
Period2/1/152/4/15

Keywords

  • Lyapunov function neural network
  • PID tuning
  • adaptive PID control
  • error backpropagation
  • first order time delay systems

ASJC Scopus subject areas

  • General Energy
  • General Engineering
  • General Computer Science

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