Robust On - Line Monitoring of Mixing Quality in Water Supply Networks

The paper applies an algorithm for recursive estimation of variables and parameters in general dynamic networks that has been developed by [Brdys 99] to robust on-line monitoring of the mixing water quality in dynamic water networks. A complete hydraulic information is assumed to be available on-line. First a parsimonious parametrisation of a mathematical model of mixing quality is derived. Next a recursive estimation algorithm is designed that uses the model and available measurements to generate on-line robust estimates of unknown quantities. The parameters and variables are estimated simultaneously. Robustness of the estimates is achieved through non-probabilistic set-bounded modelling of uncertainty in the measurement and modelling errors. The stable and tight bounds on the estimated quantities are obtained by employing a concept of moving information window. The estimation scheme is very flexible in integrating the information available. In particular, if only concentrations of the quality parameters in a network inputs are measured, the estimator operates as the quality simulator under uncertain models and not accurately known inputs. This can be viewed as a sort of generic soft sensor. Performance of the monitoring scheme is illustrated by applications to two case-study networks.