Parameter identification for nonlinear batch bio－dissimilation system of glycerol
LIU Di
WEI Shunxing
XU Gongxian
Abstract：The parameter identification for nonlinear batch bio－dissimilation system of glycerol is studied. For the nonlinear ordinary differential equation system of batch bio－dissimilation process of glycerol, a dynamic optimization problem for its parameter identification is first given by considering the sum of metabolite concentra-tion and slope errors as the optimization objective. The nonlinear ordinary differential equation system of batch bio－dissimilation process of glycerol is considered a constraint of this dynamic optimization problem. Then the ordinary differential equations of the dynamic optimization problem are approximately represented as the algebraic equations by an improved Euler method. In this way, the original dynamic optimization model is transformed as a nonlinear programming problem. Finally, a particle swarm optimization algorithm is used to solve the obtained nonlinear programming problem. Compared with the existing literatures, this paper obtained the better parameter identification results. This can provide a guide for building the nonlinear system of batch bio －dissimilation process of glycerol.
Keywords：batch bio－dissimilationparameter identificationoptimization modelimproved Euler meth-odnonlinear programmingparticle swarm optimization algorithm
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 152-158 )