Control Over Noisy Communication Media
In the past decades, control theory has been successfully applied to well-crafted closed engineering systems (e.g., automotive and aerospace industries). However, in the current technological era of ubiquitous wireless connectivity and IoT applications, the demand for control over (noisy) wireless media is rapidly growing, opening the door to numerous new challenges and opportunities. Among these is how best to communicate the time-sensitive sensing and control signals which are required to satisfy the control objective.
I will start the talk by presenting the conventional solution which breaks down the communications task into separate compression and channel coding. For control systems, stricter notions of compression and channel coding are needed: a quantizer that optimally tracks the state of the system, and a causal channel code whose error probability decays exponentially with time. I will show how to accommodate both of these demands using our newly developed efficient techniques. I will then take a more holistic approach by avoiding the digital domain altogether and using analog mappings instead. These schemes improve both the computational complexity and control performance. I will argue that these analog coding schemes are a primary example of a more general joint control-communication concept where the transmitter enjoys implicit feedback, via the control-system loop.