Performance Comparison of PID Tuning by Using Ziegler-Nichols and Particle Swarm Optimization Approaches in a Water Control System

Authors

  • Zahratul Laily Edaris Polytechnic Sultan Abdul Halim Muadzam Shah, Malaysia
  • Syariza Abdul-Rahman Universiti Utara Malaysia, Malaysia

DOI:

https://doi.org/10.32890/jict2016.15.1.10

Keywords:

Particle Swarm Optimization, PID Controller, Ziegler-Nichols, single tank water level

Abstract

Tuning the gain of Proportional-Integral-Derivative (PID) controller in a process control system is exceptionally paramount since correct tuning would help a control process response without steady state error and overshoot. As the conventional gain tuning of PID controller, the Ziegler-Nichols (ZN) approach generally delivers an enormous overshoot; therefore, current heuristics approach, namely Particle Swarm Optimization (PSO) is utilized. A tuning problem of a single tank water level dynamic control system is presented. The best PID controller parameters are determined by using the ZN and PSO approaches. Comparisons of process time performance and the performance measurement of the system are made in order to evaluate both approaches in terms of their step response through the MATLAB/Simulink platform. The results demonstrate that the PSO approach produces promising results with lower overshoot compared to the ZN approach. It is found that the PSO approach would be advantageous for the industries related to single tank water control system for a better PID gain tuning.

 

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Published

25-05-2016

Issue

Vol. 15 No. 1 (2016): Journal of Information and Communication Technology (JICT) Vol. 15, No.1 June 2016

Section

Articles

How to Cite

Edaris, Z. L., & Abdul-Rahman, S. (2016). Performance Comparison of PID Tuning by Using Ziegler-Nichols and Particle Swarm Optimization Approaches in a Water Control System. Journal of Information and Communication Technology, 15(1), 203-224. https://doi.org/10.32890/jict2016.15.1.10

Research impact

Harvested 2026-09-06
11 citations, from OpenAlex — the highest of the sources checked

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Identifiers DOI 10.32890/jict2016.15.1.10 OpenAlex W2698567378

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