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

Muhammad Saleheen Aftab; Muhammad Shafiq

doi:10.1109/IEEEGCC.2015.7060094

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

Muhammad Saleheen Aftab, Muhammad Shafiq

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 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 language	English
Title of host publication	2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781479984220
DOIs	https://doi.org/10.1109/IEEEGCC.2015.7060094
Publication status	Published - Mar 12 2015
Event	2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015 - Muscat, Oman Duration: Feb 1 2015 → Feb 4 2015

Other

Other	2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015
Country/Territory	Oman
City	Muscat
Period	2/1/15 → 2/4/15

Keywords

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

ASJC Scopus subject areas

Energy(all)
Engineering(all)
Computer Science(all)

Access to Document

10.1109/IEEEGCC.2015.7060094

Cite this

Aftab, MS & Shafiq, M 2015, Adaptive PID controller based on Lyapunov function neural network for time delay temperature control. in 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015., 7060094, Institute of Electrical and Electronics Engineers Inc., 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015, Muscat, Oman, 2/1/15. https://doi.org/10.1109/IEEEGCC.2015.7060094

@inproceedings{7c1860595b5b49ef912443161f9c2036,

title = "Adaptive PID controller based on Lyapunov function neural network for time delay temperature control",

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.",

keywords = "adaptive PID control, error backpropagation, first order time delay systems, Lyapunov function neural network, PID tuning",

author = "Aftab, {Muhammad Saleheen} and Muhammad Shafiq",

year = "2015",

month = mar,

day = "12",

doi = "10.1109/IEEEGCC.2015.7060094",

language = "English",

isbn = "9781479984220",

booktitle = "2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015 ; Conference date: 01-02-2015 Through 04-02-2015",

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AU - Aftab, Muhammad Saleheen

AU - Shafiq, Muhammad

PY - 2015/3/12

Y1 - 2015/3/12

N2 - 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.

AB - 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.

KW - adaptive PID control

KW - error backpropagation

KW - first order time delay systems

KW - Lyapunov function neural network

KW - PID tuning

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DO - 10.1109/IEEEGCC.2015.7060094

M3 - Conference contribution

AN - SCOPUS:84929104618

SN - 9781479984220

BT - 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015

Y2 - 1 February 2015 through 4 February 2015

ER -

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

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Keywords

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