On top of that, those blocksets are already optimized. The simplicity of MATLAB fuzzy control, where the SIMULINK blocksets could be used directly. In fact, we have currently applied more than 125 rules and still the margin is open. The huge number of rule one could implement. The choice of SIMULINK fuzzy control blocksets was considered very carefully for several reasons. And luckily, we find the solution in MATLAB, through SIMULINK fuzzy control blocksets. To apply this strategy we had to look for the best possible solution. This space is divided into a limited number of memberships, and the control for each membership could be easily tuned separately. The membership space of the pH is restricted between zero and fourteen where pH between zero and seven is acid and between seven and fourteen is base. So there is no need to model the system continuously, with each pH space, so the change of the pH characteristic does not influence the control strategy. The fuzzy control does not require any transfer function, nor any tedious mathematical analysis. Certainly its use in controlling pH is feasible.This is due two reasons: It provides the optimum environment for microorganism activity between pH 6.5 and 7.5 introduces his famous paper on fuzzy logic and control, fuzzy logic control has been widely implemented successfully in many industrial applications ranging from home appliances such as washing machines to heavy industries such as loading and unloading very heavy loads in ports efficiently by minimizing the action time. Wastewater neutralization plays an important part in a wastewater treatment process.
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