摘要
为更好地实现智能稳定平台隔离扰动的性能,本文针对平台载体运动姿态的预测问题展开研究.在对平台载体横滚运动时间序列进行混沌特性判定的基础上,使用加权一阶局域法对载体运动姿态进行多步预测.针对预测过程中误差累积的问题,提出在姿态预测的同时对误差序列进行预测,并通过误差预测值实时修正姿态预测值.文中给出了两种误差补偿的多步预测方法,通过试验水池的实测数据仿真分析表明,误差补偿的加权一阶局域多步预测方法提高了预测精度,抑制了误差的累积;进一步通过相对均方误差等指标进行评价,指出预测方法中LPC法误差补偿的多步预测效果最优,具有一定的实用价值.
In order to get a better performance of interference isolation, the prediction of platform carrier motion attitude was studied in the paper. After judging the chaotic characteristics of time series, multi-step prediction of roll attitude was carried out with weighted one-order local-region method. Aiming at the problem of error cumulating in predicting process, error series predicting was carried out while time series predicting, and the roll attitude predicting values were compensated by error predictions in time. Two methods of multi-step predicting with error compensation were given in the paper, and the simulating results of experimental cistern datum show that the predicting precision of the weighted one-order local-region method with error compensation is improved, and that the error cumulating is controlled. Furthermore with the relative mean square error as the evaluating index, the paper points out that the multi-step prediction with LPC compensation is the best and it is valuable for practice.
出处
《测试技术学报》
2012年第1期15-19,共5页
Journal of Test and Measurement Technology
关键词
稳定平台
混沌时间序列
加权一阶局域法
多步预测
误差补偿
stabilized platform
chaotic time series
weighted one-order local-region method
multi-step prediction
error compensation
