摘要
针对非线性系统的滤波问题,无法使用Kalman滤波器,扩展的Kalman滤波器虽能应用于非线性系统,但给出的是状态的有偏估计,并且对模型误差的鲁棒性较差。为了给出更好的参数估计值,该文将介绍一种强跟踪滤波器。强跟踪滤波器由扩展的Kalman滤波器改造而来。设计强跟踪滤波的思想是:使得残差序列在每一步相互正交,提取残差序列中所有有用的信息,用作对现时刻系统状态的估计。该文采用该滤波方法为某机动飞机控制设计了滤波器,最后对该机动飞机控制系统进行了滤波仿真研究。仿真结果表明,所设计的滤波方法对非线性系统具有良好的滤波功能。
For nonlinear system filtering problem, Kalman filter cannot be used. Though extended Kalman filter can be used in nonlinear system, but the outcome of the filter is a partial estimation and the system is not very robust. To get better parameter estimation, a filtering method, named STF (Strong Tracking Filter), is introduced. The filter is evolved from extended Kalman filter (EKF). The idea of the filter is to make discrepancy orthogonal at each step and get useful information from the discrepancy series as current state estimation. Based on the method, filter for a plane control system with white noises was designed. Simulation shows that the filtering method has better performance than traditional. The calculation cost is relatively low, and the method can be used on line.
出处
《计算机仿真》
CSCD
2004年第8期17-19,共3页
Computer Simulation
关键词
强跟踪滤波
非线性系统
飞行控制
仿真
Strong tracking filter
Nonlinear system
Flight control
Simulation
