Multimodel software sensor for a harvested fish population system

This paper deals with the problem of software sensor (state estimation) to study the continuous age structured model of a harvested fish population, in order to get an estimation of the biomass of fishes by age class. In our case the fishing effort is considered as a control term, the age classes as a states and the quantity of captured fish as a measured output. The continuous non-linear model is first represented by a Takagi-Sugeno multimodel. Next, we develop a technique for designing a multimodel software sensor (called also observer) corresponding to this system and show its asymptotic convergence. The design conditions are given in linear matrix inequalities (LMI) terms which can be solved efficiently using existing numerical tools. The simulation results demonstrate the effectiveness of the proposed method.