**4. Discussion and conclusions**

Finally, let's conclude this chapter by discussing a real online example where it is required to bring the pH from 3 to 7. This example was chosen to show how the fuzzy controller has successfully solved oscillation due to titration curve mentioned earlier. Using all the expertise to set the membership functions as well as the rules, plus a fine tuning process, the membership function is shown in figure (27), and the pH response is shown in figure (28). It is clear that the pH has been brought from 3 to 7 in a very smooth manner. This value has been confirmed through the pH meter reading.

As a general conclusion, due to non linearity inherent in the chemical waist, the study presented here has shown that using fuzzy logic control is probably best suited to control the pH of industrial waist, despite the expertise required to fine tune the controller as well as the time required. It has also been shown that no matter how the linear controllers are tuned especially PID, including the many restrictions, plus the delays and settling time for each disturbance, their action was not satisfactory. Finally, the study has also shown that implementing the fuzzy control technique, by careful selection of memberships and setting the right rules, it is possible to bring any waist pH to neutrality smoothly in an acceptable time, regardless if the waist is strong base nature or strong acidic or not.

**Figure 27.** First membership function

266 MATLAB – A Fundamental Tool for Scientific Computing and Engineering Applications – Volume 1

This section performs the task of converting the output of inference mechanism, the rules that are fired, and the DoS given by the fuzzification module into a signal to the control valve. For this, it uses "height defuzzification" which is computationally simple and

Finally, let's conclude this chapter by discussing a real online example where it is required to bring the pH from 3 to 7. This example was chosen to show how the fuzzy controller has successfully solved oscillation due to titration curve mentioned earlier. Using all the expertise to set the membership functions as well as the rules, plus a fine tuning process, the membership function is shown in figure (27), and the pH response is shown in figure (28). It is clear that the pH has been brought from 3 to 7 in a very smooth manner. This value has

As a general conclusion, due to non linearity inherent in the chemical waist, the study presented here has shown that using fuzzy logic control is probably best suited to control the pH of industrial waist, despite the expertise required to fine tune the controller as well

**3.5. Defuzzification** 

**4. Discussion and conclusions** 

been confirmed through the pH meter reading.

fast.

**Figure 28.** First test online at set point 7
