A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems

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Ambreesh Kumar 1,* Rajneesh Sharma 2

1. EC Department, Mewar University, Rajasthan, India

2. Division of Instrumentation & Control Engineering, NSIT, New Delhi, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2018.05.03

Received: 15 May 2017 / Revised: 2 Jun. 2017 / Accepted: 11 Jun. 2017 / Published: 8 May 2018

Index Terms

Fractional systems, Oustaloup Approximation, Fuzzy PID Control, Genetic Algorithm assisted Fractional Order PID Controller


This work aims at designing a fractional Proportional-Integral-Derivative controller wherein we hybridize a genetic algorithm based fractional Proportional-Integral-Derivative controller with a fuzzy logic Proportional-Integral-Derivative controller. We attempt at optimizing the fractional order Proportional-Integral-Derivative controller parameters by incorporating a Genetic Algorithm based mechanism. Thereafter, the optimized genetic algorithm based fractional Proportional-Integral-Derivative control is further fine tuned and hybridized to a fuzzy Proportional-Integral-Derivative control. Here, fuzzy logic based inference mechanism is used to tackle system uncertainties and use of rule firing strengths produces an adaptive control. Genetic Algorithm has been used to generate the most optimal controller by a natural selection of the fittest. Amalgamating Genetic Algorithm and fuzzy control approaches on fractional order systems produces a highly efficient and noise tolerant control regime. We give simulation results and compare our hybrid approach against conventional and fractional Proportional-Integral-Derivative approaches on various integer and fractional order systems (with dead time) to elucidate its superiority and effectiveness.

Cite This Paper

Ambreesh Kumar, Rajneesh Sharma, "A Genetic Algorithm based Fractional Fuzzy PID Controller for Integer and Fractional order Systems", International Journal of Intelligent Systems and Applications(IJISA), Vol.10, No.5, pp.23-32, 2018. DOI:10.5815/ijisa.2018.05.03


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