Multi‐Variable Direct Self‐Organizing Fuzzy Neural Network Control for Wastewater Treatment Process. Issue 2 (21st September 2018)

• Record Type: Journal Article
• Authors: Zhang, Wei; Qiao, Jun‐fei
• Is Part Of: Asian journal of control. Volume 22:Issue 2(2020)
• Page Start: 716
• Page End: 728
• Publication Date: 2018-09-21
• Subjects: Multi‐variable control -- neural network -- self‐organizing structure -- wastewater treatment; Automatic control -- Periodicals; Control theory -- Periodicals; 629.805
• DOI: 10.1002/asjc.1919
• Languages: English
• ISSNs: 1561-8625

Abstract

Abstract: 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.