Control of DO level in a river under uncertainty

Abstract

A previously developed regionalized sensitivity analysis for exposing critical uncertainties in models of environmental systems is extended to study control of systems for which there is a good deal of uncertainty in the mathematical model used to describe the appropriate physical, chemical, and biological processes. The method is based on a binary classification of Monte Carlo simulation results as being either satisfactory or unsatisfactory in terms of controller performance. Contrasts in parameters associated with the two classes are elucidated by statistical analysis. This allows the selection of a set of control parameters that maximizes the probability of acceptable behavior in the presence of uncertainty in process parameters. The method is applied to the problem of regulating the discharge from a lagoon with the object of preventing DO from falling below a predetermined standard. It was found that for this system the desired behavior of the controlled process can be achieved with a probability of 0.84 with a particularly simple controller design. Nevertheless, the results suggest that even modest levels of uncertainty in the process parameters can have a considerable effect on the controller performance and that additional attention should be devoted to the design of robust controllers for environmental systems.