Stochastic Control with Stale Information--Part I: Fully Observable Systems

Soleymani, Touraj; John, S Baras; Karl, H Johansson

doi:10.48550/arxiv.1810.10983

Cited by 2 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Proof: We begin the proof by observing that the triggering policies defined in (21) can also be written only as function primitive random variable and preceding triggering policies. For a given system i ∈ {1, .…”

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

“…Remark 2: In the remainder of this article we will assume that the scheduling policies are independent of the control actions and function of primitive random variable as in (21). As pointed out in [15], since the scheduling policies (21) are independent of the past control actions, the controller has no dual effect. It should be noted that the resulting closed-loop system is not optimal in general since a controller with dual effect may result in lower cost [15], [14].…”

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

“…Moreover, let d[j] = 1 for j > 1. Under the admissible scheduling policies (21), solving Problem 1 is equivalent to solving the Bellman-like equation…”

Section: A Problem Decompositionmentioning

confidence: 99%

“…. , L} is actually agnostic of any other scheduler j such that j < j − 1, the scheduling policy in (21) can then be rewritten as…”

Section: A Problem Decompositionmentioning

confidence: 99%

See 4 more Smart Citations

Distributed Value of Information in Feedback Control over Multi-hop Networks

Abara¹,

Hirche²

2021

Preprint

View full text Add to dashboard Cite

Recent works in the domain of networked control systems have demonstrated that the joint design of medium access control strategies and control strategies for the closed-loop system is beneficial. However, several metrics introduced so far fail in either appropriately representing the network requirements or in capturing how valuable the data is. In this paper we propose a distributed value of information (dVoI) metric for the joint design of control and schedulers for medium access in a multi-loop system and multi-hop network. We start by providing conditions under certainty equivalent controller is optimal. Then we reformulate the joint control and communication problem as a Bellman-like equation. The corresponding dynamic programming problem is solved in a distributed fashion by the proposed VoI-based scheduling policies for the multi-loop multi-hop networked control system, which outperforms the well-known time-triggered periodic sampling policies. Additionally we show that the dVoI-based scheduling policies are independent of each other, both loop-wise and hop-wise. At last, we illustrate the results with a numerical example.

show abstract

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

Section: Optimal Certainty Equivalence Controllermentioning

confidence: 99%

“…Moreover, let d[j] = 1 for j > 1. Under the admissible scheduling policies (21), solving Problem 1 is equivalent to solving the Bellman-like equation…”

Section: A Problem Decompositionmentioning

confidence: 99%

“…. , L} is actually agnostic of any other scheduler j such that j < j − 1, the scheduling policy in (21) can then be rewritten as…”

Section: A Problem Decompositionmentioning

confidence: 99%

See 3 more Smart Citations

Distributed Value of Information in Feedback Control over Multi-hop Networks

Abara¹,

Hirche²

2021

Preprint

View full text Add to dashboard Cite

show abstract

Minimizing Age of Information for an Energy Harvesting Source with Updating Failures

Feng

Yang

2018

2018 IEEE International Symposium on Information Theory (ISIT)

View full text Add to dashboard Cite

Consider an energy harvesting (EH) sensor that continuously monitors a system and sends time-stamped status update to a destination. The sensor harvests energy from nature and uses it to power its updating operations. The destination keeps track of the system status through the successfully received updates. With the recently introduced information freshness metric "Age of Information" (AoI), our objective is to design optimal online status updating policy to minimize the long-term average AoI at the destination, subject to the energy causality constraint at the sensor. Due to the noisy channel between the sensor and the destination, each transmitted update may be erased with a fixed probability, and the AoI at the destination will be reset to zero only when an update is successfully received. We first consider status updating without feedback available to the sensor and show that the Best-effort Uniform updating (BU) policy is optimal in a broadly defined class of online policies. We then investigate status updating with perfect feedback to the sensor and prove similar optimality of the Best-effort Uniform updating with Retransmission (BUR) policy. In order to prove the optimality of the proposed policies, for each case, we first identify a lower bound on the long-term average AoI among a broad class of online policies, and then construct a sequence of virtual policies to approach the lower bound asymptotically. Since those virtual policies are sub-optimal to the original policy, the original policy is thus optimal.

show abstract

Stochastic Control with Stale Information--Part I: Fully Observable Systems

Cited by 2 publications

References 0 publications

Distributed Value of Information in Feedback Control over Multi-hop Networks

Distributed Value of Information in Feedback Control over Multi-hop Networks

Minimizing Age of Information for an Energy Harvesting Source with Updating Failures

Contact Info

Product

Resources

About