Abstract:
Reachability traditionally thinks about the controllability Grammian of a system, i.e. the actuation vectors as they pass through the plant dynamics. This perspective dep...Show MoreMetadata
Abstract:
Reachability traditionally thinks about the controllability Grammian of a system, i.e. the actuation vectors as they pass through the plant dynamics. This perspective depends on fully knowing the future plant dynamics even as we apply controls in the present, since the ability to plan is important for control. This paper explores a toy model with uncertain random actuation vectors. Our ability to plan is modulated by how much we can anticipate about the plant's future actuation. The results here philosophically build on the concept of “control capacity” introduced earlier and the model itself is inspired by earlier work on intermittent Kalman filtering and problems of networked control with packet drops. A simple greedy strategy is optimal for our toy model and we can easily characterize the informational value of knowing future actuation vectors. Furthermore, the control capacity of the toy system can be stated in a way that is suggestive of a dimensional-sense of “signal-to-noise-ratio”.
Published in: 2016 IEEE 55th Conference on Decision and Control (CDC)
Date of Conference: 12-14 December 2016
Date Added to IEEE Xplore: 29 December 2016
ISBN Information: