自适应卡尔曼滤波器在机器人控制中的应用

Application Research of Adaptive Kalman Filter in Robot Control

机器人控制系统在实际工作中不可避免地要受到随机噪声的影响,当噪声的统计特性已知时,可以考虑采用常规Kalman滤波以抑制随机噪声对控制性能的影响;但当噪声的统计特性不完全已知时,常规Kalman滤波的滤波性能会下降甚至会引起发散。根据机器人的动态特性,设计了一个自适应Kalman滤波器,并对该滤波器应用于机器人控制系统进行了仿真实验研究。仿真结果表明,所设计的滤波器能够较好地抑制方差和均值未知的测量噪声对机器人控制系统的影响,控制系统的动态性能得到了较大的改善。

Robot control system is influenced inevitably by random noise during its running. When statistical property of random noise is known, general kalman filter can be adopted to hold back effect of measurement noise on control performance. When statistical property of random noise is not all known completely, filter performance would drop and even result in divergence. Based on the dynamics nonlinearities of robot manipulator, a adaptive kalman filter is designed and applied to robot control system in simulation research. Simulation results show that the designed filter can hold back effect of measurement noise with unknown variance and mean on robot control system,and that the dynamic performance of control system is improved.