小型无人直升机悬停状态下的系统辨识

System Identification on Small-scale Unmanned Helicopter

提出了一种渐消记忆的最小二乘逐状态辨识算法,相对原来利用最小二乘进行无人直升机矩阵辨识的方法,该算法能极大地减小计算量,降低计算的复杂程度以提高计算过程的稳定性。并采用该方法建立了小型无人直升机系统的ARMAX模型和M IMO模型,还通过仿真对2种模型做了对比,结果显示M IMO模型能更精确地描述小型无人直升机系统。

This paper presents a fading memory based least squares identification method. Compared with the traditional system identification method applied on small scale unmanned helicopter, this method can reduce processing load and improve processing stability during identification. ARMAX model and MIMO model of small scale unmanned helicopter are sonstructed in this way and then do simulation on the models. The result shows that model of MIMO is more precise on representing the helicopter system.