一类非线性系统辨识的参数空间优化遗传算法

Nonlinear System Identification with Genetic Algorithms

提出一种用于非线性系统辨识的具有较强参数空间优化能力的遗传算法 ,给出一种新的复合型变异算子 ,并设计相应的选择策略 ,较好解决了非线性系统辨识中的“维数灾难”问题。实验研究结果表明 。

Based on the genetic algorithms and the Volterra series model, a new identification method of nonlinear system with powerful ability of P space optimization is proposed. A solution to the dimension disaster is created with a new multiplex mutate and a special select. The simulation and experiment results indicate that the new method has high accuracy and robustness.