# Probabilistic state transfer, estimation and measures for optimal actuator/sensor placement for linear systems with packet dropouts

## TL;DR

This paper develops probabilistic conditions for state transfer and estimation in linear systems with packet dropouts, and proposes measures for optimal actuator and sensor placement considering data loss.

## Contribution

It introduces necessary and sufficient probabilistic conditions for state transfer and estimation under packet dropouts, and proposes new measures for optimal actuator and sensor placement.

## Key findings

- Derived probabilistic measures for actuator/sensor placement
- Established conditions for state transfer and estimation with packet dropouts
- Demonstrated influence of dropout probabilities on actuator placement

## Abstract

We consider linear systems subject to packet dropouts and obtain necessary and sufficient conditions for an arbitrary state transfer and state estimation over a finite time instance $T$. The data loss signal is modeled using the Bernoulli random variable. We leverage properties of the Hadamard product in our approach and use the derived necessary and sufficient conditions to compute the probability that an arbitrary state transfer is possible at a specified time instant. Similarly, the probability of finding an exact state estimate is found using the observability counterparts of the results. Using the necessary and sufficient conditions obtained for the invertibility of the Gramian, we give new probabilistic measures for optimal actuator and sensor placement problems and obtain optimal/sub-optimal solutions. We demonstrate by an example how the probabilities of packet dropouts influence the choice of an optimal actuator. We also discuss how to implement feedback laws and the LQR problem for these models involving packet dropouts.