Self-Tuning Pid Neural Network Controller to Control Nonlinear Ph Neutralization in Waste Water Treatment

Abstract

89AbstractThe conventional PID control (linear) is popular control scheme that is used in almost pH control at waste water treatment process. pH model with respect to titration liquid flow rate has been known to be intrinsically difficult and nonlinear, especially when the process is conducted to non-linear range pH reference (pH 4-8), the settling time reach a long time. Therefore in this paper the nonlinear controller with self-tuning PID scheme is performed handle pH by training a neural-network based on backpropagation error signals. The pH process model is combination between CSTR (Continuous Stirred Tank Reactor) linear dynamic with H 3 PO 4 , HF, HCl, H 2 S flow rate and nonlinear static electro neutrality (wiener process model). The simulation result has a good and suitable performance under several tests (set-point and load change). The simulation result show the pH control system can follow the change of pH set-point and load with the average steady state error 0.00034. The settling time achieved at 50 second faster than conventional PID controller scheme.

Nonlinear pH Control Based on Reaction Invariant and Self-Tuning PID Controller

“…In order to capture the characteristics of the pH process, experiment and simulation-using Eq. (1)- (14) was done by adding HCl with NaOH (1-750 mL) and can see in Fig. 3.…”

“…Combining equation (1), (9) and (10) ] for the total ionic concentration of the base (the reaction invariant variable), Fa, Fb are the acid, base flow rate Ca, Cb is the acid, base concentration and V is the CSTR liquid volume [11], [12], [13], [14]. …”

Neural Network-Based Self-Tuning PID Control for Underwater Vehicles

“…Their performance is described as accurate when uncertainty and perturbations take place while performing a trajectory. Although the training periods are extremely long, there are also combinations of PID controls and a smart system aimed to auto-tune the gains of different systems such as: sub-aquatic [ 15 , 16 ], non linear [ 17 , 18 , 19 , 20 , 21 , 22 ], and others: [ 23 , 24 , 25 , 26 ].…”