Enzymatic Reaction Model Parameter Estimation of Biodiesel Synthesis Using Particle Swarm Optimization

Abstract

The increasing number of vehicles and industries that emit exhaust gas emissions that cause air pollution close to the threshold of a dangerous man. Oil exploration major cause rapid depletion of petroleum. The discovery of biodiesel provides an alternative solution to the above, because biodiesel can reduce exhaust emissions and is a renewable alternative energy. Synthesis biodiesel can be done through an enzyme reaction that utilizes so-called biodiesel synthesis enzymatic reaction. Valid model enzymatic reaction is the key in the process of biodiesel synthesis reaction. This enzymatic reaction model contains the parameters to be estimated. Therefore, the determination of the parameters (parameter estimation) is an important enzyme kinetic. Parameter estimation can be performed using local optimization algorithms, but this algorithm has the major drawback is the optimal value obtained is a local optimal value. Therefore, in this research have been applied to global optimization algorithm, Particle Swarm Optimization for parameter estimation because it has the ability to find solutions quickly. Based on the simulation results obtained by the best parameter estimates as follows: k₁=0.05000000000, k₂=0.11000000000, k₃=0.215000000000, k₄=1.22799999999995, k₅=0.24200000000000, k₆=0.007000000000 and Sum Square Error is 2.51 x 10^-27.