Abstract
The effluent ammonia and total nitrogen variation lead to multiple operating conditions in wastewater treatment process (WWTP), which challenges the control strategies based on a single control model. Therefore, it is essential to design suitable control strategies for WWTP to enhance the control performance under different operating conditions. In this paper, an adaptive type-2 fuzzy-neural switching control (AT2FSC) strategy is proposed to solve this problem. First, a soft-sensing model is developed based on fuzzy neural network and influent data in WWTP to estimate the effluent ammonia nitrogen and total nitrogen status. Then, the online operating conditions are determined by the critical values of effluent ammonia nitrogen and total nitrogen. Second, the corresponding fuzzy rules are devised for different operating conditions and a type 2 fuzzy switching model (AT2FSM) is constructed to capture the operating status changes of WWTP. Then, the proposed AT2FSC can design the switching control strategy according to AT2FSM to adapt to the current operating condition. Third, the Lyapunov theorem ensures the stability of the proposed AT2FSC method. Then, it facilitates the further application of AT2FSC in WWTP. Finally, the performance of AT2FSC under various operating conditions is validated on the benchmark simulation model No.1 (BSM1). Simulation results under four different operating conditions demonstrate that the proposed AT2FSC strategy can reduce the excess peak of effluent ammonia and total nitrogen while maintaining the operating performance.
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