02554nam a2200265 a 4500 vtls000018947 KUKTEM 20251114204410.0 070323t2006 my f m 000 0 eng d THE0003552(Local) 201905152106 zulaiha 201107132215 VLOAD 200908141310 VLOAD 200908141241 VLOAD 200703231658 farina UMP TJ213 .M64 2006 rs Thesis Mohd Fadzli Mohd Noris Comparison between ziegler-nichols and cohen-coon method for controller tunings / Mohd Fadzli Bin Mohd Noris Kuantan, Pahang : KUKTEM , 2006 xii, 58 p. : ill. (some col) ; 30 cm. + 1 computer disc Project paper (Bachelor of Chemical Engineering) -- Kolej Universiti Kejuruteraan dan Teknologi Malaysia - 2006 Bibliography: p. [41]-42 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. Parameter estimation Control Control theory Automatic control 0 0 0 1 10000 10000 2019-09-04 0 TJ213 .M64 2006 rs Thesis 0000021650 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 2091 | TJ213 .M64 2006 rs Thesis 0000021651 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 1375 1381 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992