Fuzzy pid based Temperature Control of Electric Furnace for Glass Tempering Process
Comparison of different PID tuning mechanisms
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4.1.1 Comparison of different PID tuning mechanisms
Table 4.1 summarizes the continuous and discrete PID controllers tuned by Ziegler-Nichols tuning algorithm and MATLAB/ pid tuning extension tool box. , Table 4.1 summarizes the transient response comparison of PID controllers tuned by Ziegler-Nichols, Cohen-Coon, Integral of time-weighted absolute error (ITAE) both load point and set point changes and MATLAB/ pid tuning extension tool box. Rise time Pick time Settling time Overshoot Continuous Ziegler-Nichols 22s 42.1s 220s 58% Discrete Ziegler- Nichols 21s 35.5s 150s 44% MATLAB pid tuning extension tool 56s 112s 210s 16.129% Table 4. 1 summarizes of continuous and discrete PID controller step response Table 4. 2 Summarizes of PID controller step response with different tuning mechanism Mechanism Rise time Pick time Settling time Overshoot Ziegler- Nichols 23s 37.3s 110s 24% Cohen-Coon 26s 50.2s 270s 69% ITAE set point change 32s 61s 150s 19% ITAE load point change 23.1s 37.3s 150s 56% MATLAB pid tuning extension tool 56s 112s 210s 16.129% Fuzzy PID Based Temperature Control of Electric Furnace for Glass Tempering Process M.Sc. Thesis, Addis Ababa University, December 2016 57 As shown in figure 4.2 and table 4.2 the discrete controller is better in transient performance analysis. Because of glass tempering process needs the controller that has minimum overshoot, we use parameters of PID tuned by MATLAB pid tuning extension tool for our MATLAB/SIMULINK model and farther simulation studies. Download 1.99 Mb. Do'stlaringiz bilan baham: 
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