Multimodel robust observer for an uncertain fish population model

In this paper, a new method is proposed to design an observer for a nonlinear and uncertain system describing a continuous stage structured model of a harvested fish population. The aim is to get an estimation of the biomass of fishes by stage class. In the studied model the fishing effort is considered as a control term, the stage classes as states and the quantity of captured fish as a measured output. A Takagi-Sugeno multimodel first represents the uncertain non-linear model. Next, we develop a technique for designing a multimodel observer corresponding to this system, which attenuates the effect of modelling uncertainties and measurement noise on the state estimation. The design conditions are given in linear matrix inequalities (LMIs) terms that can be solved efficiently using existing numerical tools. The validity of the proposed method is illustrated by the simulation results.