Scalable scheduling algorithms for wireless networked control systems

A MIMO Multi-hop Control Network (MCN) consists of a MIMO LTI system where the communication between sensors, actuators and computational units is supported by a (wireless) multi-hop communication network, and data flow is performed using scheduling and routing of sensing and actuation data. We provide necessary and sufficient conditions on the plant dynamics and on the communication protocol configuration such that the problem of Fault Detection and Isolation (FDI) of failures and malicious attacks to communication nodes can be solved.

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“…, i p } ⊆ ℓ. By (5), (6), and since in (V, E)Ũ andỸ are bridge nodes that do not belong to any cycle, (20) implies the following:…”

Section: Fdi Of Node Failures On Mcnsmentioning

confidence: 98%

Fault detection and isolation of malicious nodes in MIMO Multi-hop Control Networks

D’Innocenzo

Benedetto

Smarra

2013

52nd IEEE Conference on Decision and Control

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“…8 Although these weights are technically time varying (i.e., they depend on k), we use this notation for simplicity. 9 We will address these assumptions later in this section. …”

Section: Wcn With Observer Style Updatesmentioning

confidence: 99%

“…Here, IID implies that the random variables {ξji[k]} k≥0 are IID. 9 For each link, these random processes map each transmitted value tji into a received value ξji[k]tji (see Fig. 4).…”

Section: Wcn With Observer Style Updatesmentioning

confidence: 99%

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Closing the loop: A simple distributed method for control over wireless networks

Pajić

Sundaram

et al. 2012

2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN)

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We present a distributed scheme used for control over a network of wireless nodes. As opposed to traditional networked control schemes where the nodes simply route information to and from a dedicated controller (perhaps performing some encoding along the way), our approach, Wireless Control Network (WCN), treats the network itself as the controller. In other words, the computation of the control law is done in a fully distributed way inside the network. We extend the basic WCN strategy, where at each time-step, each node updates its internal state to be a linear combination of the states of the nodes in its neighborhood. This causes the entire network to behave as a linear dynamical system, with sparsity constraints imposed by the network topology. We demonstrate that with observer style updates, the WCN's robustness to link failures is substantially improved. Furthermore, we show how to design a WCN that can maintain stability even in cases of node failures. We also address the problem of WCN synthesis with guaranteed optimal performance of the plant, with respect to standard cost functions. We extend the synthesis procedure to deal with continuoustime plants and demonstrate how the WCN can be used on a practical, industrial application, using a processin-the-loop setup with real hardware. KeywordsCooperative control, decentralized control, networked control systems, wireless sensor networks ABSTRACTWe present a distributed scheme used for control over a network of wireless nodes. As opposed to traditional networked control schemes where the nodes simply route information to and from a dedicated controller (perhaps performing some encoding along the way), our approach, Wireless Control Network (WCN), treats the network itself as the controller. In other words, the computation of the control law is done in a fully distributed way inside the network. We extend the basic WCN strategy, where at each time-step, each node updates its internal state to be a linear combination of the states of the nodes in its neighborhood. This causes the entire network to behave as a linear dynamical system, with sparsity constraints imposed by the network topology. We demonstrate that with observer style updates, the WCN's robustness to link failures is substantially improved. Furthermore, we show how to design a WCN that can maintain stability even in cases of node failures. We also address the problem of WCN synthesis with guaranteed optimal performance of the plant, with respect to standard cost functions. We extend the synthesis procedure to deal with continuoustime plants and demonstrate how the WCN can be used on a practical, industrial application, using a process-in-the-loop setup with real hardware.

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“…The case study was to design a wireless control network for an industrial plant that controls mineral processing of ores. A description of the plant and the details of the control parameters is given in [37]. In the context of the present paper, it is enough to say that the part of the plant that we considered contains 17 control loops: 9 air flow, 6 pulp level and 2 reagent.…”

Section: Case Study: a Mineral Floatation Control Problemmentioning

confidence: 99%

Compositional Modeling and Analysis of Multi-Hop Control Networks

Alur

D’Innocenzo

Johansson

et al. 2011

IEEE Trans. Automat. Contr.

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108

105

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Abstract-We propose a mathematical framework for modeling and analyzing multi-hop control networks designed for systems consisting of multiple control loops closed over a multi-hop (wireless) communication network. We separate control, topology, routing, and scheduling and propose formal syntax and semantics for the dynamics of the composed system, providing an explicit translation of multi-hop control networks to switched systems. We propose formal models for analyzing robustness of multi-hop control networks, where data is exchanged through a multi-hop communication network subject to disruptions. When communication disruptions are long, compared to the speed of the control system, we propose to model them as permanent link failures. We show that the complexity of analyzing such failures is NP-hard, and discuss a way to overcome this limitation for practical cases using compositional analysis. For typical packet transmission errors, we propose a transient error model where links fail for one time slot independently of the past and of other links. We provide sufficient conditions for almost sure stability in presence of transient link failures, and give efficient decision procedures. We deal with errors that have random time span and show that, under some conditions, the permanent failure model can be used as a reliable abstraction. Our approach is compositional, namely it addresses the problem of designing scalable scheduling and routing policies for multiple control loops closed on the same multi-hop control network. We describe how the translation of multi-hop control networks to switched systems can be automated, and use it to solve control and networking co-design challenges in some representative examples, and to propose a scheduling solution in a mineral floatation control problem that can be implemented on a time triggered communication protocols for wireless networks.Index Terms-Compositional analysis, multi-hop sensor and actuator networks, networked control.

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Scalable scheduling algorithms for wireless networked control systems

Cited by 21 publications

References 12 publications

Fault detection and isolation of malicious nodes in MIMO Multi-hop Control Networks

Fault detection and isolation of malicious nodes in MIMO Multi-hop Control Networks

Closing the loop: A simple distributed method for control over wireless networks

Compositional Modeling and Analysis of Multi-Hop Control Networks

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