Scheduling networked state estimators based on Value of Information

Molin, Adam; Esen, Hasan; Johansson, Karl Henrik

doi:10.1016/j.automatica.2019.108578

Cited by 28 publications

(36 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…determined from (17). Furthermore, the probability of successful transmission over each wireless link is known and timeinvariant.…”

Section: B Stability Analysismentioning

confidence: 99%

“…Try-once-discard (TOD) is one of the most well-known schemes of this type which, at each frame, allocates the channels to the subsystems with the largest discrepancy between the true and estimated state values [15]. For the linear quadratic Gaussian (LQG) control problem, value of information (VoI), which contained the current observations for the network [16], was proposed as the priority measure and algorithms were provided for determining the priorities by using a rollout strategy [16], [17]. Equivalently, the term cost of information loss (CoIL) was coined in [18] for the cost of losing information for a general setup and, unlike the VoI in [16], [17], it is associated with the statistical properties of the observations.…”

Section: Introductionmentioning

confidence: 99%

“…For the linear quadratic Gaussian (LQG) control problem, value of information (VoI), which contained the current observations for the network [16], was proposed as the priority measure and algorithms were provided for determining the priorities by using a rollout strategy [16], [17]. Equivalently, the term cost of information loss (CoIL) was coined in [18] for the cost of losing information for a general setup and, unlike the VoI in [16], [17], it is associated with the statistical properties of the observations. For decoupled systems, it was shown in [18] that minimizing the linear quadratic cost is equivalent to prioritizing channel access with respect to CoIL.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Timer-Based Distributed Channel Access for Control Over Unknown Unreliable Time-Varying Communication Channels

Farjam

Charalambous

Wymeersch

2019

2019 18th European Control Conference (ECC)

View full text Add to dashboard Cite

We consider the resource allocation problem for a system consisting of multiple control subsystems that share an unknown unreliable time-varying wireless channel. We propose a novel method for granting channel access deterministically without requiring information exchange between subsystems, based on local timers for prioritizing channel access with respect to a local cost that takes into account the (initially unknown) channel conditions. We propose a novel setup which has the capability of learning the parameters of imperfect communication links while ensuring distributed collision-free implementation. More specifically, we adopt learning algorithms for estimating the channel quality and, hence, define the local cost as a function of this estimation and control performance. The efficacy of this mechanism is evaluated via simulations.

show abstract

“…determined from (17). Furthermore, the probability of successful transmission over each wireless link is known and timeinvariant.…”

Section: B Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Timer-Based Distributed Channel Access for Control Over Unknown Unreliable Time-Varying Communication Channels

Farjam

Charalambous

Wymeersch

2019

2019 18th European Control Conference (ECC)

View full text Add to dashboard Cite

show abstract

“…Over the last two decades, there have been many attempts from the control and the communication communities to develop, evaluate, and improve such utility functions compared to the conventional fixed-period and randomized data coordination approaches. Notions such as Value-of-Information (VoI) [7,8], Age-of-Information (AoI) [9,10], and Event-Triggered (ET) [11,12], are metrics that have been separately shown to be capable of coordinating information distribution, taking into account the integrated and coupled context of NCSs. Traditionally, however, two rather distinct paths on addressing the NCS design have been followed: From the communication perspective, the focus mainly results in the design approaches that maximize the network throughput or minimize the end-to-end latency and jitter often ignoring the dynamics, requirements, and characteristics of the sending and receiving entities and the specific data that are being transmitted [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Where Freshness Matters in the Control Loop: Mixed Age-of-Information and Event-Based Co-Design for Multi-Loop Networked Control Systems

Mamduhi

Champati

Gross

et al. 2020

JSAN

View full text Add to dashboard Cite

In the design of multi-loop Networked Control Systems (NCSs), wherein each control system is characterized by heterogeneous dynamics and associated with a certain set of timing specifications, appropriate metrics need to be employed for the synthesis of control and networking policies to efficiently respond to the requirements of each control loop. The majority of the design approaches for sampling, scheduling, and control policies include either time-based or event-based metrics to perform pertinent actions in response to the changes of the parameters of interest. We specifically focus in this article on Age-of-Information (AoI) as a recently-developed time-based metric and threshold-based triggering function as a generic Event-Triggered (ET) metric. We consider multiple heterogeneous stochastic linear control systems that close their feedback loops over a shared communication network. We investigate the co-design across the NCS and discuss the pros and cons with the AoI and ET approaches in terms of asymptotic control performance measured by Linear-Quadratic Gaussian (LQG) cost functions. In particular, sampling and scheduling policies combining AoI and stochastic ET metrics are proposed. It is argued that pure AoI functions that generate decision variables solely upon minimizing the average age irrespective of control systems dynamics may not be able to improve the overall NCS performance even compared with purely randomized policies. Our theoretical analysis is validated through several simulation scenarios.

show abstract

“…distributed observers can be consulted in [14]. Regarding to Kalman filters, in [15], a decentralized Kalman filter is used to address the localization of a multiple-robot problem; [16] discusses three distributed Kalman filter algorithms, one of them focused on a cooperative and recursive estimation that combines the consensus strategy and Kalman filtering; [17] focuses on the scheduling of data in a networked system; and [18] develops a method based on linear matrix inequalities (LMIs) to compute the Kalman filter, being this method implemented in [19] for multi-robot localization purposes. Note that LMIs have become a major way of formulating a vast variety of control and estimation problems [20].…”

mentioning

confidence: 99%

An LMI-Based Design Method for Modular Observers

Martín

Muros

Masero

et al. 2020

2020 European Control Conference (ECC)

View full text Add to dashboard Cite

A linear matrix inequality approach for designing a family of observers suitable for systems with variable communication topologies is presented. In particular, the observer is composed of blocks associated to the status of the communication links, providing increasing performance as more links are enabled. The error boundaries for topology switchings are analyzed both for the presented observer and for a specific Kalman filter for each topology. Finally, a simulation example is used to illustrate the feasibility of the proposed method. I. INTRODUCTIONIn the last decades, distributed schemes have gained relevance in the field of control and estimation due to their wellknown advantages such as scalability, modularity, ease of implementation, and robustness, which make them appropriate for large-scale networked systems [1], and other complex approaches [2]. Distributed architectures are characterized for being composed of a set of subsystems, governed by agents that have access to local information. Consequently, communication is needed to gather information from the rest of the system to carry out estimation and control tasks in the most efficient way [3]. Reshaping the topology of the communication network according to the necessities of the system provides additional flexibility to optimize performance. In this way, only communication channels that really contribute to the improvement of the task are enabled (see, e.g., [4], [5] for cooperative approaches).Through the observers, variables such as the system state, disturbances, noises, etc., can be estimated in the cases in which they cannot be measured directly [6]. Some classical estimators, e.g., the Luenberger filter [7], settled the basis for most observers designed nowadays. Also, the Kalman filter, which introduced white noise in the filtering formulation to offer optimal solutions [8], [9], has been widely studied and extended over the years [10]. Recently, both approaches have been adapted to noncentralized systems requirements. Some distributed Luenberger approaches for linear systems are explored in: [11], with a given fixed communication architecture between subsystems; [12], where time-varying communication topologies are considered; and [13], where consensus between subsystems is used to estimate the nonlocally detectable portion of the state. More details about

show abstract

Scheduling networked state estimators based on Value of Information

Cited by 28 publications

References 14 publications

Timer-Based Distributed Channel Access for Control Over Unknown Unreliable Time-Varying Communication Channels

Timer-Based Distributed Channel Access for Control Over Unknown Unreliable Time-Varying Communication Channels

Where Freshness Matters in the Control Loop: Mixed Age-of-Information and Event-Based Co-Design for Multi-Loop Networked Control Systems

An LMI-Based Design Method for Modular Observers

Contact Info

Product

Resources

About