STATE-SPACE IDENTIFICATION FOR NONLINEAR SYSTEMS BASED ON GENETIC ALGORITHM

A nonlinear state-space identification method based on genetic algorithm has been proposed in this paper. It is shown that the problem of such systems that cannot be identified by classical least-square has been solved by genetic algorithms and perfect nonlinear state-space identification results can be obtained when the dimension of state and the nonlinear degree are low. Meanwhile, it has been pointed out that state dimension confirmation, significant term selection and insignificant term deletion in this method still need to be researched further.