Copyright eEl IF AC Advanced Control of Chemical Processes, Pisa, Italy, 2000 ROBUSTNESS ANALYSIS OF MODEL PREDICTIVE CONTROL OF ACTIVATED SLUDGE PLANTS S.R. Weijers and H. A. Preisig Systems f3 Control Group Faculty of Applied Physics, Eindhoven University of Technology Cascade 3.14, p.a. Box 513 NL-5600 MB Eindhoven The Netherlands Email: S.R.WeijersCtue.nl Abstract: Process control is considered an important means to meet the increasingly tighter demands that are being placed on sewage treatment in most western countries, especially with respect to nutrients. This paper investigates stability robustness of a wastewater treatment plant controlled with Model Predictive Control (MPC). Aims of this model study are to study possibilities and limitations of advanced control application to wastewater treatment , to obtain insight in the process factors that affect control system robustness, and to find tuning rules to improve MPC robustness. A simple plant model was studied. A structured uncertainty description of parameter and state uncertainty was used to avoid conservative results. ;.t-Analysis was used to compute robustness bounds of the closed loop system. The results show that achievable robustness improvement by tuning is limited and indicate that nonlinearity has a stronger effect on stability than parameter errors. Copyright © 2000IFAC Keywords: Bio control, Wastewater treatment , Predictive control, Robust control, Structured singular value, 1. INTRODUCTION Increasingly stringent demands are being put onto nitrogen removal from wastewater. Munici- pal wastewater is treated biologically in so-called activated sludge plants. To meet the stricter de- mands, plants have to be upgraded and the treat- ment process becomes more complicated. Pro cess control is generally considered as an important means to achieve stable operation under the typ- ically large variations in load and temperature . This view and recent advances in modelling and sensor technology have been the motivation for significant research efforts in different countries to develop effective control strategies. One particular question of interest is how and to which extent advanced control can contribute to improved plant operation and decreased in- 545 vestment costs. The activated sludge process is multivariable, nonlinear, time-variable and stiff, input constraints are present, and load and tem- perature vary considerably. It is difficult to find controllers that cope with all these characteristics, and currently different control laws are applied, proposed and investigated, ranging from classical control including cascade control, model based control such as LQG and MPC, adaptive control to rule-based control, including knowledge-based control and fuzzy control. The currently available knowledge in the form of mathematical models, especially the well-known Activated Sludge Model No. 1 (ASM1, (Henze et al ., 1987)) suggests the application of model based control. In previous work, application of MPC to different waste water treatment systems was studied (Weijers et al., 1995)(Weijers et al., 1997) ,