Event-triggered control under time-varying rates and channel blackouts
For control engineers designing networked control systems, this work enables stable operation under realistic channel conditions including blackouts, though the assumption of prior channel knowledge limits practical applicability.
This paper addresses event-triggered stabilization of linear systems over time-varying rate-limited channels with blackouts, achieving exponential stabilization at a desired rate despite intermittent communication loss. The proposed algorithm provides a lower bound on data capacity for a deterministic time-slotted channel model.
This paper studies event-triggered stabilization of linear time-invariant systems over time-varying rate-limited communication channels. We explicitly account for the possibility of channel blackouts, i.e., intervals of time when the communication channel is unavailable for feedback. Assuming prior knowledge of the channel evolution, we study the data capacity, which is the maximum total number of bits that could be communicated over a given time interval, and provide an efficient real-time algorithm to lower bound it for a deterministic time-slotted model of channel evolution. Building on these results, we design an event-triggering strategy that guarantees Zeno-free, exponential stabilization at a desired convergence rate even in the presence of intermittent channel blackouts. The contributions are the notion of channel blackouts, the effective event-triggered control despite their occurrence, and the analysis and quantification of the data capacity for a class of time-varying continuous-time channels. Various simulations illustrate the results.