首页 | 本学科首页   官方微博 | 高级检索  
     

基于最优信息融合卡尔曼滤波的预测控制算法
引用本文:刘冠良,刘晓华. 基于最优信息融合卡尔曼滤波的预测控制算法[J]. 烟台师范学院学报(自然科学版), 2009, 0(1): 14-17
作者姓名:刘冠良  刘晓华
作者单位:鲁东大学数学与信息学院,山东烟台264025
基金项目:国家自然科学基金(60774016)
摘    要:针对噪声环境下的线性时不变系统,给出了基于最优信息融合卡尔曼滤波的预测控制算法.运用线性最小方差意义下的最优信息融合卡尔曼滤波方法获得状态估计,进而得到输出的N步超前预测值,最后通过最小化二次性能指标获得基于信息融合状态估计的控制输入.仿真实例验证了算法的有效性.

关 键 词:预测控制  信息融合  卡尔曼滤波

Predictive Control Algorithm Based on Optimal Information Fusion Kalman Filter
LIU Guan-liang,LIU Xiao-hua. Predictive Control Algorithm Based on Optimal Information Fusion Kalman Filter[J]. Yantai Teachers University journal(Natural Science Edition), 2009, 0(1): 14-17
Authors:LIU Guan-liang  LIU Xiao-hua
Affiliation:( School of Mathematics and Information, Ludong University, Yantai 264025, China)
Abstract:Aiming at the linear time-invariant system under noise condition, predictive control algorithm is presented based on optimal information fusion Kalman filter. By using the optimal information fusion Kalman filter in the linear minimum variance sense, the state estimators are derived. Further more,N steps ahead output pre- dictions are obtained. Finally, the control inputs based on information fusion state estimators are calculated by minimizing the quadratic cost. A simulation example illustrates the efficiency of this method.
Keywords:predictive control  information fusion  Kalman filter
本文献已被 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号