Fuzzy model and decision of COD control for an activated sludge process
Fuzzy Sets and Systems
Information Sciences—Informatics and Computer Science: An International Journal
Knowledge-Based Clustering: From Data to Information Granules
Knowledge-Based Clustering: From Data to Information Granules
Database design and querying within the fuzzy semantic model
Information Sciences: an International Journal
Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems
Information Sciences: an International Journal
Takagi-Sugeno fuzzy model based indirect adaptive fuzzy observer and controller design
Information Sciences: an International Journal
Identification of transparent, compact, accurate and reliable linguistic fuzzy models
Information Sciences: an International Journal
Hi-index | 0.07 |
This paper is concerned with predicting the chemical oxygen demand, the common criterion of the outlet water in most wastewater treatment plants. A fuzzy modeling approach is proposed which can efficiently eliminate the complex nonlinear terms existing in Activated Sludge Model No. 1 (ASM1). First, the structure of fuzzy rules in the approach is identified based on ASM1. Further, by combining the well-known fuzzy c-means cluster algorithm and the method of least squares, the fuzzy space of input variables required in the approach is partitioned and the consequent parameters are identified using the data in Benchmark Simulation Model No. 1, which can be replaced by the data in a real wastewater treatment plant. The effectiveness of the proposed approach is illustrated by comparing the predicted values of chemical oxygen demand and the experimental measurements obtained from the Benchmark Simulation Model No. 1.