Subspace-based optimal control of n-removal activated sludge plants

A multivariable feedforward/state-feedback linear-quadratic (LQ) + (I) controller is designed and used to control the NO_x-N concentration (nitrate-nitrogen plus nitrite-nitrogen) in both anoxic and aerobic zones of a pre-denitrifying activated sludge process. The controller design is based on a discrete state-space model of the process, and it incorporates integral error and anti-reset windup. The state-space model was obtained using a subspace-based identification technique, from the input/output data. The "artificial" states generated by the subspace algorithm are estimated online through a Kalman filter and coupled with the LQ-controller. This technique is evaluated through simulations using the ASWWTP-USP benchmark and the results obtained show the potential efficiency of the proposed approach