Article ID Journal Published Year Pages File Type
7121201 Measurement 2018 22 Pages PDF
Abstract
It is difficult to estimate the water quality of the wastewater treatment process, because the operating conditions are frequently changed. This paper gives an effective adaptive estimation method, which uses Hammerstein with wavelet neural networks, adaptive weighted fusion, and approximate linear dependence (ALD) analysis. Adaptive stable learning algorithm for the local Hammerstein with wavelet neural networks is proposed. A novel synchronous learning of fusion weighs is discussed. On-line calibration of operating centers with ALD improves the estimation accuracy. The experimental results show that the proposed estimation method for the water quality COD (Chemical Oxygen Demand) is satisfied compared with the laboratory results even when the operating conditions are changed frequently.
Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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