The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Design of Modeling & Simulator for ASP Realized with the Aid of Polynomiai Radial Basis Function Neural Networks

다항식 방사형기저함수 신경회로망을 이용한 ASP 모델링 및 시뮬레이터 설계

  • Kim, Hyun-Ki (Dept. of Electrical Engineering, The University of Suwon) ;
  • Lee, Seung-Joo (Dept. of Electrical Engineering, The University of Suwon) ;
  • Oh, Sung-Kwun (Dept. of Electrical Engineering, The University of Suwon)
  • Received : 2012.05.17
  • Accepted : 2013.01.17
  • Published : 2013.04.01
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Abstract

In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.

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References

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