摘要
采用自适应预测控制的方法对带有随机时延的网络化控制系统进行分析和研究.针对网络化控制系统中的随机时延,首先利用自回归模型对其进行建模,再采用基于最速下降法的最小均方差算法对此随机时延进行跟踪预测,然后将预估的时延作为已知的信息,对网络化控制系统模型的时变参数进行辨识调整,最终实现对网络化控制系统的自适应预测控制.仿真结果表明:所采用的控制方法能明显地改善系统的输出,显著减小随机时延对网络化控制系统所造成的不利影响.
In this paper,a novel adaptive predicted control method was proposed to analyze NCS(networked control system) with random delays.An auto-regressive model was firstly used to model the random delays in such NCS. Then an LMS(least mean square) algorithm based on steepest descent algorithm was adopted to track and estimate these delays.Parameter identification and adaptive predicted control method were used to compensate the random delays existing in such NCS on the assumption that these predicted delays in this NCS were known already.Simulation was done which shows that the control method introduced in this paper could improve system outputs significantly so that the adverse effects caused by random delays were greatly reduced.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2009年第S1期292-296,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(60574088
60874053)
关键词
网络化控制系统
随机时延
自回归模型
参数辨识
自适应预测控制
networked control system
random delays
auto-regressive model
parameter identification
adaptive predicted control
