Affiliations: [a]
College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
| [b]
School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China
| [c] Beijing Key Laboratory of Computational Intelligence and Intelligence System, Beijing, China
Correspondence:
[*]
Corresponding author. Junfei Qiao, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China. Tel.: +861067391631; Fax: +861067396226; E-mail: isibox@sina.com.
Note: [1] This work was supported by the National Science Foundation of China under Grants 61533002, 61225016, and 61203099, by the Beijing Municipal Natural Science Foundation under Grant 4122006, and by the Ph.D. Program Foundation from the Ministry of Chinese Education under Grant 20121103120020.
Abstract: In order to improve the accuracy and adaptive ability of dissolved oxygen concentration control in the wastewater treatment process (WWTP), a self-organizing fuzzy control (SOFC) method is developed in this paper. The main feature of this control system is that the fuzzy controller can extract fuzzy rules automatically using a self-organizing fuzzy neural network (FNN), which can adjust the network structure during the process based on the growing-pruning-combining algorithm. Furthermore, to ensure the convergence of the system, a compensation controller is designed to dispel the FNN approximation error, and the parameter compensation is also considered while adjusting the network structure. Finally, simulation results, based on the international benchmark simulation model No.1 (BSM1), demonstrate that the proposed method can achieve better control performance and superior adaptive ability compared with PID, model predictive control and conventional fuzzy logic controller.
