网络控制系统的模糊权重变采样周期调度策略

摘要

Performance of the networked control system is affected by the sampling period .For the networked control system with multi loop ,according to the system contpol loop error and error rate ,dynamic weights are calculated by using fuzzy inferential for each control loop ,new network utilization is predicted based on the current network status .Then ARIMA algorithm is used to predict the packet transmission time .Finally ,under the conditions of the network bandwidth is limited ,fuzzy dynamic weight coeffi-cient ,network utilization ,packet transmission time is used for constantly changing sampling period of the system control loop ,to op-timize the performance of networked control system .True Time toolbox simulation result demonstrates the effectiveness of this method .%网络控制系统的性能受到采样周期的影响。针对多回路网络控制系统，根据系统控制回路误差和误差变化率，利用模糊推理计算各回路的动态权重，同时根据当前网络运行状况预测新的网络利用率，然后利用ARIMA算法对数据包传输时间进行预测，最后在网络带宽一定的条件下，利用模糊动态权重系数、网络利用率、数据包传输时间，不断的改变系统中各控制回路的采样周期，达到优化网络控制系统性能的目的。利用True Time工具箱进行的仿真验证了本文方法的有效性。