Event triggered nonlinear model predictive control for a wastewater treatment plant

Abstract

This paper presents an event triggered nonlinear model predictive control (NMPC) to improve the performance of a wastewater treatment plant (WWTP). The goal of this paper is to design a simplified event triggered NMPC(ETNMPC) suitable for practical implementation. Unlike the conventional NMPC where an optimisation problem is solved at each sampling instant, in the proposed event based formulation of NMPC, the optimisation problem is re-evaluated only when a certain triggering condition is satisfied. A triggering condition is designed based on deviation of error or one step ahead prediction of error from a predefined threshold value. If one of these goes beyond the predefined threshold limit or the time gap from the triggering of last event crosses the maximum allowable time limit, a new event is triggered. The controller is designed to improve the overall performance of a WWTP by regulating two significant variables, i.e. nitrate and dissolved oxygen concentrations at some specified set-points. A conventional NMPC is also designed. The performances of the proposed controller is compared with a conventional NMPC and PI controller. Both NMPC and ETNMPC are able to improve Effluent Quality and Overall Cost Index of the WWTP when compared with PI controller, but a significant reduction in computation and communication(almost 50%) is achieved in the case of ETNMPC when compared with the conventional NMPC.