Abstract

Wireless networks are replacing Field buses in Discrete manufacturing and Process control because they:

• Avoid wiring costs,
• Are simpler to install,
• Are simpler to maintain, and,
• Potentially, allow deploying more sensors and actuators.

However, wireless channels have limited bandwidth and fluctuating delivery rates.

Bandwidth limits are Packet rate limits. Under such limits, it is important to communicate measurement samples and control updates at times when such communication has the most value. Hence, Event-triggered (ET) sampling strategies are more efficient than periodic sampling. When the network delivers packets reliably, ET schemes are superior because the `silence’ between successive samples encodes useful information.

The best sampling schemes are solutions of Optimal stopping problems. For sampling scalar linear systems over an infinite horizon with a limit on the average sampling rate, Delta sampling is optimal. For finite horizons, it is not. Moreover its behaviour on finite horizons has some counter-intuitive and unexplained phenomena. We will also see that, unlike under periodic sampling, ET sampling for control is more complicated than ET sampling for state estimation.

Fluctuating delivery rates cause some samples to be lost. For the state estimation problem, we will see whether the loss of some samples will destroy the superiority of ET sampling.