Adaptive smooth observer design for state estimation in Desulfovibrio alaskensis 6SR cultures

in this work the dynamics of a sulfate reducing bacteria is predicted by estimating the biomass concentration and sulfide production using only sulfate (substrate) concentration measurements. the estimation process is developed on batch, fed-batch and continuous cultures of desulfovibrio alaskensis 6sr, where a mathematical dynamic model of the bioreactor is presented and tuned with experimental data. the design of the adaptive smooth state observer takes into account the model's system structure and an adaptive gain of the output feedback which contain a hyperbolic tangent of the estimation error, an theoretical frame is provide in order to show the convergence characteristics of the proposed method. the results of the proposed estimation methodology are generated via numerical simulation in order to show its performance.