Sequential filter for river pollution monitoring

Abstract

A sequential least squares filter LS developed to estimate the pollution in a multisectional river. The Nash game approach proposed by Ozgliner and Perkins (lB78) is applied. The sections 0.1'0 defined uooording to mouths of larger tributaries. Streetor-Phelps hyperbolic equations model the contents of dissolved oxygen and its demand. The problem is defined as simultaneous minimization of quadratic estimation funct.ionals defined on successive sections. The resulting decentralized filter looks like a cascade of local filters, each of which, besides measurements of its own section, uses those of preceding ones. Thus the filters are informed in advance if pollution occurs upstream. An orthogonal collocation approximation is applied to develop a numerical solution.