基于小生境遗传算法的多维传感器动态解耦方法

Dynamic Decoupling Method for Multi-Axis Sensor Based on Niche Genetic Algorithm

多维传感器的动态耦合是指某一方向的动态输出信号中,含有其他方向输入量的影响,该项误差是影响传感器测量精度的一个重要因素。基于小生境遗传算法,提出了多维传感器动态解耦方法。该方法利用传递函数矩阵分析法的解耦思想,可以根据多维传感器的标定数据,应用系统辨识方法和小生境遗传算法直接求解解耦网络并进行优化,克服了原经典方法中对传感器模型精确已知的要求,具有一定的鲁棒性。仿真结果证明了该方法的正确性和有效性。

The dynamic coupling of a multi-axis sensor is defined as a situation that the output signal of one direction includes the additional value, which affected by the input in other direction. Obviously, the dynamic coupling error will decrease the sensor measurement precision seriously. A new multi-axis sensor dynamic decoupling method is proposed based on a niche genetic algorithm. The method first gets the calibration data of the multi-sensor, and then uses the system identification method and the niche genetic algorithm to calculate and optimize the decoupling network based on the analysis method of transform function matrix. In addition, it also avoids the high precision requirement of the sensor model in the traditional dynamic decoupling method. Finally, the simulation results show the correctness and the affectivity of the proposed method.