Self-Organizing Fuzzy Terminal Sliding Mode Control for Wastewater Treatment Processes

Wastewater treatment process is a complex industrial process with disturbance and strong nonlinearity, and it is difficult to accurately track the pre-designed dissolved oxygen (DO) concentration in finite time. In this paper, a self-organizing fuzzy terminal sliding mode (SOFTSM) control strategy is proposed to solve this problem. First, a terminal sliding mode controller (TSMC) is designed to obtain a control law and achieve the finite time tracking of the pre-designed DO concentration. Second, a self-organizing fuzzy neural network (SOFNN) is utilized to estimate the nonlinear term. Then, the pruning strategy without pre-setting pruning threshold is designed to improve the approximation accuracy and further ensure the accuracy of control performance. Third, an adaptive law and robust control term are designed to reduce the influence of uncertainty and approximation error. Moreover, the stability of SOFTSM and the characteristic of finite time convergence are proved. Finally, the proposed method is tested on the benchmark simulation model no. 1 (BSM1). In contrast to other existing methods, SOFTSM can realize accurate control of DO concentration in finite time.

Automated summary

In this paper, a self-organizing fuzzy terminal sliding mode (SOFTSM) control strategy is proposed to accurately track the dissolved oxygen (DO) concentration in wastewater treatment process. The method combines terminal sliding mode controller, self-organizing fuzzy neural network, and adaptive law, and is tested on a benchmark simulation model.