Dynamic model prediction control for an activated sludge model based on a T-S multi-model

This paper investigates the use of Dynamic Model Control (DMC) on an Activated Sludge Reactor. The reduced bio-reactor activated sludge ASM1 model, which describes the biological degradation of an activate sludge reactor, is designed based on several simplifications, as a Takagi Sugeno fuzzy model (TS). The TS model structure is based on a set of linear sub models, covering the process input-output space, interpolated by a nonlinear weighting function. In the case of the ASM1 model, as specified in this paper, the system equations are available in the form with the input being u. The DMC control law developed is based on the system having input Δu, and therefore the input system needs to be modified prior to the control formulation design. The classical Multi-Input Multi-Output (MIMO) DMC formulation is then modified to integrate the TS formulation as the controller internal model. The simulation results show the effectiveness of the proposed DMC controller compared to benchmark PID in terms of error and response dynamics.