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  • 标题:Self-Tuning Pid Neural Network Controller to Control Nonlinear Ph Neutralization in Waste Water Treatment
  • 其他标题:Self-Tuning Pid Neural Network Controller to Control Nonlinear Ph Neutralization in Waste Water Treatment
  • 本地全文:下载
  • 作者:Hendra Cordova ; Andry F. Wijaya
  • 期刊名称:Majalah Iptek = IPTEK : The Journal for Technology and Science
  • 印刷版ISSN:0853-4098
  • 电子版ISSN:2088-2033
  • 出版年度:2007
  • 卷号:18
  • 期号:3
  • DOI:10.12962/j20882033.v18i3.168
  • 语种:English
  • 出版社:IPTEK
  • 摘要: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 H3PO4, HF, HCl, H2S 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.
  • 关键词:pH Neutralization; PID Controller; Backpropagation Training; Neural Network
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