An adaptive control method for the dissolved oxygen concentration in wastewater treatment plants

The activated sludge process plays a vital role in the treatment of the civil wastewater. In the operation of the activated sludge process, a key variable is dissolved oxygen (DO) concentration. In this paper, a neural nonlinear adaptive control design technique is presented to solve the DO concentration control problem for an uncertain wastewater treatment process. In the controller design, all uncertain dynamics of the wastewater treatment are approximated by using radial basis function neural networks. Then, it is rigorously proved that semiglobal uniform ultimate boundedness of all the closed-loop system signals is guaranteed by the Lyapunov method. Finally, simulation studies are performed to demonstrate the effectiveness of the proposed adaptive controller. Comparing with the existing controllers, simulation results show that a satisfactory performance is obtained using the proposed adaptive controllers.