Adaptive Control for Nitrate Nitrogen with Time Delays Based on Recurrent Fuzzy Neural Network

The wastewater treatment process is a sophisticated operation characterized by pronounced nonlinearity, uncertainty, and time-delay properties. The nitrate nitrogen concentration is identified as the primary challenge in meeting total nitrogen standards. To achieve precise control, an adaptive control method based on a recurrent fuzzy neural network with time delays is proposed. Initially, the recurrent fuzzy neural network is utilized to effectively identify the unknown dynamic parameters in the wastewater treatment process. Subsequently, the time-delay model of the denitrification process is established, and the Lyapunov-Krasovskii functional is applied to mitigate time-varying delays. Finally, the stability of the designed controller is theoretically proven. By utilizing Benchmark Simulation Model 1 simulation, the superior control performance is further verified.