Incorporating emergency alarms in reliable wireless process control

Li, Bo; Nie, Lei; Wu, Chengjie; González, Humberto; Lu, Chenyang

doi:10.1145/2735960.2735983

Cited by 53 publications

(27 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some works of the real-time scheduling problem of IWSANs (e.g., [28]- [31]) do not address aperiodic and unpredictable data flows. Additionally, although the works [32] and [33] consider how to schedule aperiodic and unpredictable data flows, too much interference is introduced into other flows.…”

Section: Related Workmentioning

confidence: 99%

A Hierarchical Data Transmission Framework for Industrial Wireless Sensor and Actuator Networks

Jin

Kong

et al. 2017

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

Abstract-A smart factory generates vast amounts of data that require transmission via large-scale wireless networks. Thus, the reliability and real-time performance of large-scale wireless networks are essential for industrial production. A distributed data transmission scheme is suitable for large-scale networks, but is incapable of optimizing performance. By contrast, a centralized scheme relies on knowledge of global information and is hindered by scalability issues. To overcome these limitations, a hybrid scheme is needed. We propose a hierarchical data transmission framework that integrates the advantages of these schemes and makes a tradeoff among real-time performance, reliability, and scalability. The top level performs coarse-grained management to improve scalability and reliability by coordinating communication resources among subnetworks. The bottom level performs fine-grained management in each subnetwork, for which we propose an intrasubnetwork centralized scheduling algorithm to schedule periodic and aperiodic flows. We conduct both extensive simulations and realistic testbed experiments. The results indicate that our method has better schedulability and reduces packet loss by up to 22% relative to existing methods.

show abstract

Section: Related Workmentioning

confidence: 99%

A Hierarchical Data Transmission Framework for Industrial Wireless Sensor and Actuator Networks

Jin

Kong

et al. 2017

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

show abstract

“…WCPS supports cosimulation of control systems implemented in Simulink and WSAN implemented in TOSSIM. WCPS has previously been used for realistic case studies of wireless structural control systems [20,31], of wireless process control systems [19], and it was recently used to build a benchmark problem for wireless structural control released to the civil engineering community [32].…”

Section: Case Study Designmentioning

confidence: 99%

“…The WirelessHART stack includes a multichannel TDMA MAC layer, a real-time transmission scheduler, and a routing layer supporting source routing and graph routing [19]. We have implemented the asymmetric routing framework that allows any com- binations of source and graph routing strategies to be used for sensing and actuation.…”

Section: Implementation Of Wsanmentioning

confidence: 99%

“…On the control side the system integrates an observer based on an Extended Kalman Filter with a model predictive controller and an actuator with a buffer for recent control inputs. The case study is implemented in the Wireless Cyber-Physical Simulator (WCPS) [19,20] that integrates Simulink with a Wire-lessHART protocol stack based on a realistic wireless model and on traces collected from a real-world wireless testbed. Our experiments demonstrate that a wireless control system can have different levels of resilience to packet loss for sensing and actuation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wireless Routing and Control: A Cyber-Physical Case Study

Li¹,

Ma²,

Westenbroek

et al. 2016

2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)

Self Cite

View full text Add to dashboard Cite

Wireless sensor-actuator networks (WSANs) are being adopted in process industries because of their advantages in lowering deployment and maintenance costs. While there has been significant theoretical advancement in networked control design, only limited empirical results that combine control design with realistic WSAN standards exist. This paper presents a cyberphysical case study on a wireless process control system that integrates state-of-the-art network control design and a WSAN based on the WirelessHART standard. The case study systematically explores the interactions between wireless routing and control design in the process control plant. The network supports alternative routing strategies, including single-path source routing and multi-path graph routing. To mitigate the effect of data loss in the WSAN, the control design integrates an observer based on an Extended Kalman Filter with a model predictive controller and an actuator buffer of recent control inputs. We observe that sensing and actuation can have different levels of resilience to packet loss under this network control design. We then propose a flexible routing approach where the routing strategy for sensing and actuation can be configured separately. Finally, we show that an asymmetric routing configuration with different routing strategies for sensing and actuation can effectively improve control performance under significant packet loss. Our results highlight the importance of co-joining the design of wireless network protocols and control in wireless control systems. * The first two authors contributed equally to this work.

show abstract

“…Computer-based simulations have been widely used in network design and analysis, which requires repeatable comparisons among various network scenarios and alternative solutions [24]. Simulations are also widely used to evaluate complex systems, such as cyber-physical systems, by cosimulating behaviors of component systems/networks in a hierarchical High-Level Architecture (HLA) [25], [26].…”

Section: Introductionmentioning

confidence: 99%

A simulation framework for industrial wireless networks and process control systems

Liu

Candell

Lee

et al. 2016

2016 IEEE World Conference on Factory Communication Systems (WFCS)

View full text Add to dashboard Cite

Factory and process automation systems are increasingly employing information and communications technologies to facilitate data sharing and analysis in integrated control operations. Wireless connections provide flexible access to a variety of field instruments and reduce network installation and maintenance costs. This serves as an incentive for the adoption of industrial wireless networks based on standards such as the WirelessHART and ISA100.11a in factory control systems. However, process control systems vary greatly and have diverse wireless networking requirements in different applications. These requirements include deterministic transmissions in the shared wireless bandwidth, low-cost operation, long-term durability, and high reliability in the harsh radio propagation environment.It is an open question whether a generic wireless technology would meet the requirements of industrial process control. In this paper, we propose a novel simulation framework for performance evaluation of wireless networks in factory and process automation systems. We select a typical process control plant model, specifically the Tennessee Eastman Challenge (TE) Model, and define the interfaces between the process simulator and the wireless network simulator. We develop a model of the protocol stack of the WirelessHART specification in the OMNET++ simulation engine as a typical industrial wireless network. We present simulation results that validate the prospect of using WirelessHART in the TE plant, and we evaluate the impact of various wireless network configurations on the plant operation. Given its modular design, the proposed simulation framework can be easily used to evaluate the performance of other industrial wireless networks in conjunction with a variety of process control systems.Index Terms-industrial wireless networks, sensor networks, factory and process automation networks, WirelessHART, network simulation.

show abstract

Incorporating emergency alarms in reliable wireless process control

Cited by 53 publications

References 30 publications

A Hierarchical Data Transmission Framework for Industrial Wireless Sensor and Actuator Networks

A Hierarchical Data Transmission Framework for Industrial Wireless Sensor and Actuator Networks

Wireless Routing and Control: A Cyber-Physical Case Study

A simulation framework for industrial wireless networks and process control systems

Contact Info

Product

Resources

About