六维力传感器下E膜小生境野草EKF滤波研究.pdf

62 2015 ，51（18） Computer Engineering and Applications 计算机工程与应用 六维力传感器下E 膜小生境野草EKF 滤波研究 朱文超，许德章 ZHU Wenchao, XU Dezhang 安徽工程大学 机械与汽车工程学院，安徽 芜湖 241000 College of Mechanical and Automotive Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, China ZHU Wenchao, XU Dezhang. Research for lower E-type membrane of six-axis force sensor based on NIWO-EKF. Computer Engineering and Applications, 2015, 51 （18）：62-68. Abstract ：To reduce the influence of the noise for the measurement accuracy of the six-axis force sensor and solve the problem that the Extended Kalman filtering can ’t gain the optimal system noise matrix, a new Extended Kalman Filtering （EKF ）based on Niche Invasive Weed Optimization （NIWO ）has been proposed. The nonlinear state-space model based on the relationship between the response of sinusoidal excitation force and the strain has been established. The idea of the grass breeding has been introduced to achieve the Gauss sampling of system interference matrix consisted of first six-order vibration mode information and to produce the initial feasible solutions. After combining niche technology with Invasive Weed Optimization （IWO ）, the global search of the new algorithm has been executed by the IWO. According to fitness value, the individual has been arranged in descending order. Multiple populations can be carved out to collaborate on the basis of the capacity of the niche. The search processing can be avoided to fall into local optimum. The improved invasive weed optimization algorithm is introduced to optimize the system ’s noise matrix in EKF. The simulation results indicate that the new algorithm has better robustness and real-time performance. It can effectively enhance the measurement accu- racy of six-axis force sensor. Key words ：six-axis force sensor; lower E-type membrane; invasive weed optimization; niche technology; extended Kal- man filtering 摘 要：为减小噪声信号对六维力传感器测量精度的影响，同时解决因主振型信息缺失导致扩展Kalman 滤波器难