Adaptive mutation differential evolution algorithm and its application to estimate soft sensor parameters
Feng Qian · Control theory & applications · 2006
A novel adaptive mutation differential evolution (ADE) algorithm containing the adaptive mutation operator, in which the mutation probability is determined according to the evolved generations, is proposed in this paper. The adaptive mutation operator makes the individuals diversity in the population at the initial generations to overcome the premature, and reduces the mutation probability gradually during the evolutionary process to preserve the excellent individuals and enhance the probability of obtained the global optimal solution. To compare the performances of ADE with those of the traditional differential evolution (DE), ADE and DE are applied to search the global optimal solution of analytical function. The results demonstrate that both ADE's on-line and off-line performances are superior to those of DE, the probability of obtained the global optimal solution is larger than that of DE, and that the parameter sensitivity degree of ADE is lower than that of DE. Furthermore, ADE is applied to estimate the model parameters of 4-carboxybenzaldehyde (4-CBA) soft sensor, and satisfactory results are obtained.