A Novel Evolutionary Tuning Method for Fractional Order PID Controller
Subhransu Padhee1, Abhinav Gautam2, Yaduvir Singh3, Gagandeep Kaur4

1Subhransu Padhee, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, India.
2Abhinav Gautam, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, India.
3Dr. Yaduvir Singh, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, India.
4Ms. Gagandeep Kaur, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, India.
Manuscript received on May 20, 2011. | Revised Manuscript received on June 10, 2011. | Manuscript published on July 05, 2011. | PP: 1-9 | Volume-1 Issue-3, July 2011. | Retrieval Number: C041051311
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: PID controller is a well known controller which is used in most control applications. Around 90% control applications use PID controller as the controlling element. The tuning of PID controller is mostly done using Zeigler-Nichols tuning method. But there are some inherent drawbacks of Ziegler-Nichols based tuning. For the optimal tuning of controller, the tuned values have to be changed using computer simulation to meet the process needs. In PID controller the derivative and the integral order are in integer. Fractional order PID (FOPID) is a special kind of PID controller whose derivative and integral order are fractional rather than integer. The key challenge of designing FOPID controller is to determine the two key parameters λ (integral order) and µ (derivative order) apart from the usual tuning parameters of PID using different tuning methods. Both λ and µ are in fraction which increases the robustness of the system and gives an optimal control. This paper proposes a novel tuning method for tuning λ and µ of FOPID using genetic algorithms.
Keywords: Fractional order PID, genetic algorithms, PID, Ziegler-Nichols.