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Comparison between ziegler-nichols and cohen-coon method for controller tunings

Mohd Fadzli, Mohd Noris (2006) Comparison between ziegler-nichols and cohen-coon method for controller tunings. Faculty of Chemical & Natural Resources Engineering, Universiti Malaysia Pahang.


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Proportional-Integral-Derivative (PID) controllers are the predominant types of feedback control. PID controller is widely used in industry due to their simplicity and easy to tuning. For controller tuning, the PID parameters are tuned by any conventional method in order to assure a good reference signal to the closed loop system is obtained by filtering appropriately the set-point step signal. This study is conducted to get the optimum PID controller parameters (,,cIDKττ) for first order process model. Two well known methods; Ziegler-Nichols (Z-N) method and Cohen-Coon (C-C) are used to tune controller. Both methods are compared to get the optimum condition for the process model with one-quarter decay ratio at minimum settling time and minimum largest error. The responses for both methods are analyzed using Simulink in MATLAB software. Block diagram for the process model with controllers was created for simulation process. Kc= 16.667, Iτ =6.283 and Dτ =1.571 are optimum parameters setting for Ziegler-Nichols method and the minimum largest error as 0.582 and minimum settling time equal with 11.8s in sample 11. For Cohen-Coon method, Kc= 14.703, Iτ =3.622 and Dτ =0.541 are optimum parameters setting. The minimum largest error and minimum settling time from response in sample 39 are 0.4914 and 12.2s. The results indicated that responses using Cohen-Coon tuning are slightly better than those with the Ziegler-Nichols settings method.

Item Type: Undergraduates Project Papers
Additional Information: Project paper (Bachelor of Chemical Engineering) -- Kolej Universiti Kejuruteraan dan Teknologi Malaysia - 2006
Uncontrolled Keywords: Parameter estimation -- Control , Control theory , Automatic control
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Chemical & Natural Resources Engineering
Depositing User: Rosfadilla Mohamad Zainun
Date Deposited: 15 Apr 2010 13:13
Last Modified: 03 Mar 2015 06:04
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