Noisy Sensor Scheduling in Wireless Networked Control Systems: Freshness or Precision

TL;DR

This paper develops a relationship between estimation error and sensor data freshness and precision, then applies it to optimize wireless sensor scheduling, resulting in improved control system performance.

Contribution

It introduces a novel functional relationship linking estimation error with data freshness and precision, and proposes a sliding window scheduling algorithm for wireless sensors.

Findings

Significant performance improvements over existing scheduling policies.

Effective handling of high freshness or precision requirements.

Validated through simulation results.

Abstract

In linear wireless networked control systems whose control is based on the system state's noisy and delayed observations, an accurate functional relationship is derived between the estimation error and the observations' freshness and precision. The proposed functional relationship is then applied to formulate and solve the problem of scheduling among different wireless links from multiple noisy sensors, where a sliding window algorithm is further proposed. The algorithm's simulation results show significant performance gain over existing policies, even in scenarios that require high freshness or precision of observations.