Call For Paper Volume:4 Issue:8 Aug'2017 |

Set Point Weight Tuning Using PID-Fuzzy Logic Controller

Publication Date : 18/06/2015

Author(s) :

Gagan Soni , Ashish Singh Thakur , Himmat Singh .

Volume/Issue :
Volume 2
Issue 6
(06 - 2015)

Abstract :

In this paper, a novel methodology, based on fuzzy logic, for the tuning of proportional-integral derivative (PID) controllers is presented. PID controllers are the most widely used controllers in the industry. Tuning of PID controllers has always been an area of active interest in the process control industry. The conventional PID controller is not very efficient due to the presence of non linearity in the system of the plant and also it has a quite high overshoot and settling time. Many tuning formulae that have been devised such as the Ziegler-Nichols one, assures a good load-disturbance attenuation, but often fail to achieve satisfactory performances, and therefore the operator has to use their experience and might fail to attain the best performances. Though ZN tunes systems very optimally, a better performance is needed for very fine response and this is obtained by using Fuzzy Logic Controller (FLC) methodology which is highly effective. This paper has two main parts. Firstly, a PID controller has been designed by using Ziegler-Nichols frequency response method and its performance has been observed. The Ziegler Nichols tuned controller parameters are fine tuned to get satisfactory closed loop performance. Secondly, for the same systems a PID–FLC has been proposed. Performance comparison between Ziegler Nichols tuned PID controller, and the proposed PID–FLC is presented. The simulation studies are then conducted based on the developed model using MATLAB and Simulation. The behavior of the system is studied in terms of time response (e.g., steady state error, rise-time, settling time, overshoot) and compare PID-FLC adverse Ziegler Nichols tuned PID controller. It found that the performance of the PID-FLC is better than Ziegler Nichols tuned PID controller.

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Set Point Weight Tuning Using PID-Fuzzy Logic Controller

June 17, 2015