基于灰色预测的网络控制系统协同优化反馈调度策略研究

Research of Co-design Feedback Scheduling Strategy for NCSs Based on Grey Prediction

研究了网络控制系统的反馈调度问题;在调度器的设计过程中,采用灰色预测方法来获取网络可利用资源,以调整网络控制系统各回路中传感器的采样周期,从而达到各回路网络资源的优化配置,有效减小网络控制系统中的诱导时延,极大地改善了动态网络环境,克服了现有静态调度方法的不足;最后,通过仿真分析证实了所提理论的有效性。

The issue of feedback scheduling for networked control systems （NCSs） is researched. By using grey prediction methodology to obtain network resource, which can be used, the dynamic feedback scheduling strategy is proposed in the process of scheduler design. And by on--line adjusting sampling period of sensors in networked control systems, the network--induced delay is reduced. Then more network resources are set for the control loop with poor performance. Thus the dynamic network environment is effectively improved, and the shortcoming of existing static scheduling is overcome. Finally, simulation examples show the effectiveness of the presented theory.