Optimization of PID Tuning Using Genetic Algorithm

  • Tengku Ahmad Faris Ku Yusoff Department of Chemical Engineering and Energy Sustainability, Faculty of Engineering, Universiti Malaysia Sarawak, Kuching, Sarawak, Malaysia
  • Mohd Farid Atan Department of Chemical Engineering and Energy Sustainability, Faculty of Engineering, Universiti Malaysia Sarawak, Kuching, Sarawak, Malaysia
  • Nazeri Abdul Rahman Department of Chemical Engineering and Energy Sustainability, Faculty of Engineering, Universiti Malaysia Sarawak, Kuching, Sarawak, Malaysia
  • Shanti Faridah Salleh Department of Chemical Engineering and Energy Sustainability, Faculty of Engineering, Universiti Malaysia Sarawak, Kuching, Sarawak, Malaysia
  • Noraziah Abdul Wahab Department of Chemical Engineering and Energy Sustainability, Faculty of Engineering, Universiti Malaysia Sarawak, Kuching, Sarawak, Malaysia
Keywords: tuning method, genetic algorithm

Abstract

Controller tuning is one of the important aspect in industry. With a good tuning method, it can ensure the quality of the process and product produce. Apart from that, it can protect the environment and help the company to reduce the cost. Genetic algorithm is one of the tuning method that increase usage and awareness in industry. Thus, the objective of this research is to compare the performance of the conventional tuning method with the performance of tuning method by using genetic algorithm can be seen. Optimization was done on stripping section of distillation column by using genetic algorithm with population size of 20, 40, 60 and 80 and comparing the result with previous optimization using Ziegler-Nichols method. The result obtain showed large improvement in the process response especially on rise time from 1.33 s to 1.31s and settling time from 4.56 to 4.46. Finally, population size of 40 deliver the fastest rise time and settling time.

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Published
2015-09-30
How to Cite
Faris Ku Yusoff, T. A., Atan, M. F., Abdul Rahman, N., Salleh, S. F., & Wahab, N. A. (2015). Optimization of PID Tuning Using Genetic Algorithm. Journal of Applied Science & Process Engineering, 2(2), 97-106. https://doi.org/10.33736/jaspe.168.2015