Dissolved oxygen control of the activated sludge wastewater treatment process using stable adaptive fuzzy control

The paper describes the development of an adaptive fuzzy control strategy for control of dissolved oxygen (DO) concentration on an activated sludge process (ASP). The technique is applied to the Benchmark Simulation Model n.1 (BSM1) which is a standard for performance assessment and evaluation of ASP control strategies. The controller uses DO concentration error feedback and manipulates the flow control valves supplying air to the bioreactor cells. The presented adaptive fuzzy controller is capable of incorporating linguistic information, assumes no mathematical model of the plant, and guarantees the global stability of the resulting closed-loop system. The design steps of this data-driven controller uses the Lyapunov synthesis approach with a parameter projection algorithm to construct an adaptive fuzzy controller. In order to guarantee the boundedness of all signals, it is proposed a new easy to design supervisory control based on a fuzzy system which does not require knowledge of the function of the plant model, may integrate human knowledge, and works in parallel with the main adaptive fuzzy controller with a smooth switching scheme between supervisory and nonsupervisory modes. The results of simulations show that this combined controller can learn and improve control rules resulting in accurate DO control.