Adaptive Multiple Sampling Rate Scheduling of Real-time Networked Supervisory Control System - Part II

Abstract

Remote supervisory control system is one type of network control systems (NCS) to perform supervisory control via communication networks. There can be information loss when information is transmitted from the remote plants to the supervisors due to the additional constraints (e.g., bandwidth limitations) by using communication networks as media. In part I of these papers, a sampling rate scheduling approach has been introduced and investigated on its potential ability of prevent the lost. Part II of these papers proposes an adaptive multiple sampling rate scheduling (AMSRS) algorithm to dynamically adjust sampling rates and allocate available bandwidths to transmit measurements from the remote plants to the supervisors. The AMSRS algorithm makes its decisions by dynamically monitoring the measurements' power spectrums and calculating the ranges of sampling rates which maintain their fidelity. And the useful information lost is minimized by adjusting the rates using a dynamic optimization approach. A two high throughput screening (HTS) processes supervisory control system is used as the case study. In the process, the measurements of the DC motor in the moving robot are used to demonstrate the effects of using this scheduling algorithm