光电跟踪伺服系统的自适应差分进化算法辨识

为了获得准确的光电跟踪伺服系统的模型，采用自适应差分进化算法对光电跟踪伺服系统进行辨识研究，该算法根据辨识误差平方和自动调整变异、交叉因子。在输入为正弦离散数字信号下辨识系统的离散模型。为了验证算法的有效性，在频域内与扫频法辨识的一、二阶模型和系统实际输出比较研究。实验结果表明:在相同正弦离散信号条件下，辨识输出与系统实际输出基本一致，与扫频法的RMSE相比减小了20.33%，二阶模型在高频段偏离系统实际输出稍大些，一阶系统输出与系统实际输出基本一致。研究结果表明，自适应差分进化算法计算量小，方法简便，辨识准确，在光电跟踪伺服控制领域具有一定的工程应用价值。

Adaptive differential evolution algorithm identification of photoelectric tracking servo system

In order to obtain an accurate model of the photoelectric tracking servo system, the identification using adaptive differential evolution algorithm based on the identification error sum was adopted. The mutation and crossover factor of the algorithm was automatically adjusted. The discrete model of system was identified under the situation of discretely sine digital signal input. Furthermore, the output of the first-order and second-order model using the sweeping frequency method in the frequency domain was compared with the output of the reality to prove the validity of the algorithm. Experimental result shows that under the same discretely sine signal input, the result of the identification is same with the real-life result and reduced about 20.33% in the RMSE compared with the sweeping frequency method. The second-order model has a bigger deviation in the high frequency domain and the first-order model has the same output with the real-life output. The adaptive differential evolution algorithm has a smaller amount of calculation and an accurate identification, besides, this method is simple enough. In summary, this method has a certain value in the engineering application.