直驱式电液伺服转叶舵机的遗传蚁群参数辨识

为了准确地获得直驱式电液伺服转叶舵机的性能参数,建立数学模型,确定系统的阶数,并在标准遗传算法的基础上,结合蚁群算法的正反馈机制提出一种新的遗传蚁群算法对模型参数进行辨识,在给定的上下界内找到一组参数使之满足对实际系统的最佳逼近,使系统在实际输入信号下能更好地复现实际系统的实际输出.采用另一组实验数据检验辨识结果对实际系统的任意实际输入输出采样数据组的逼近程度.验证结果表明,该辨识结果对实际系统的符合程度高于87%.该方法可用于一般复杂系统的实际参数辨识。

Parameter identification of direct drive electro-hydraulic servo rotary vane steering gear based on genetic ant colony algorithm

Direct drive electro-hydraulic servo rotary vane steering gear is new high efficiency energy saving and high power density steering gear.In order to obtain performance parameters of this steering gear accurately,a mathematical model for it is established,and the exponent number of the model is determine,then searching is performed for the best parameter values between the upper and lower bounds of the parameters using a new identification method based on ant colony optimization-genetic algorithm(ACO-GA).The goal is to make the calculating output approach to the experimental one.The model is also verified by another group of experimental data,and the result shows that the close ratio is over 87%,which proves that the model parameters identified are reasonable.