【摘 要】
：
针对从样本数据进行系统辨识的问题,提出一种由典型数学模型相互组合构成系统模型的新的辨识方法,将系统结构辨识问题转化为组合优化问题,并采用遗传算法同时实现了系统的结
【机 构】
：
东北大学系统工程研究所,沈阳工业大学软件学院 沈阳110004,沈阳110023
论文部分内容阅读
针对从样本数据进行系统辨识的问题,提出一种由典型数学模型相互组合构成系统模型的新的辨识方法,将系统结构辨识问题转化为组合优化问题,并采用遗传算法同时实现了系统的结构辨识与参数辨识,模拟仿真与实际系统辨识结果验证了系统辨识方法的合理性与求解算法的有效性.
Aiming at the problem of system identification from the sample data, a new identification method is proposed, which combines the typical mathematical models to form the system model. The system structure identification problem is transformed into the combinatorial optimization problem, and the genetic algorithm is used to realize the structure identification With parameter identification, simulation and actual system identification results, the rationality of the system identification method and the effectiveness of the algorithm are verified.
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