Multi‐Variable Direct Self‐Organizing Fuzzy Neural Network Control for Wastewater Treatment Process

A multi‐variable direct self‐organizing fuzzy neural network control (M‐DSNNC) method is proposed for the multi‐variable control of the wastewater treatment process (WWTP). In this paper, the proposed control system is an essential multi‐variable control method for the WWTP. No exact plant model is...

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Bibliographic Details
Published in:Asian journal of control 2020-03, Vol.22 (2), p.716-728
Main Authors: Zhang, Wei, Qiao, Jun‐fei
Format: Article
Language:English
Subjects:
Artificial neural networks
Computer simulation
Control systems
Control theory
Controllers
Decoupling
Fuzzy control
Fuzzy logic
Fuzzy systems
Multi‐variable control
Network control
neural network
Neural networks
Nonlinear systems
self‐organizing structure
Wastewater treatment
Water treatment
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Summary:A multi‐variable direct self‐organizing fuzzy neural network control (M‐DSNNC) method is proposed for the multi‐variable control of the wastewater treatment process (WWTP). In this paper, the proposed control system is an essential multi‐variable control method for the WWTP. No exact plant model is required, which avoids the difficulty of establishing the mathematics model of WWTP. The M‐DSNNC system is comprised of a fuzzy neural network controller and a compensation controller. The fuzzy neural network is used for approximating the ideal control law under a general nonlinear system. Moreover, the neural network is designed in a self‐organizing mode to adapt the uncertainty environment. Simulation results, based on the international benchmark simulation model No.1 (BSM1), demonstrate that the control accuracy is improved under the proposed M‐DSNNC method, and the controller has a much stronger decoupling ability.
ISSN:1561-8625
1934-6093
DOI:10.1002/asjc.1919