Wireless control system design and co-simulation

Björkbom, Mikael; Nethi, Shekar; Eriksson, Lasse; Jäntti, Riku

doi:10.1016/j.conengprac.2011.05.012

Cited by 29 publications

(13 citation statements)

References 28 publications

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“…Packetlevel network simulation can be achieved through the usage of ns-2 and OMNet++ which can provide high-level protocol stack implementation. The PiccSIM tool chain [8] provides an integration of Matlab/Simulink models with ns-2, allowing for control system design and automatic code generation. Similarly, NCSWT [12] integrates Matlab/Simulink and ns-2 for simulating networked control system.…”

Section: Related Workmentioning

confidence: 99%

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GISOO: A virtual testbed for wireless cyber-physical systems

Aminian¹,

Araújo²,

Johansson³

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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The increasing demand for wireless cyber-physical systems requires correct design, implementation and validation of computation, communication and control methods. Traditional simulation tools, which focus on either computation, communication or control, are insufficient when the three aspects interact. Efforts to extend the traditional tools to cover multiple domains, e.g., from simulating only control aspects to simulating both control and communication, often rely on simplistic models of a small subset of possible communication solutions. We introduce GISOO, a virtual testbed for simulation of wireless cyber-physical systems that integrates two state-of-the art simulators, Simulink and COOJA. GISOO enables users to evaluate actual embedded code for the wireless nodes in realistic cyber-physical experiments, observing the effects of both the control and communication components. In this way, a wide range of communication solutions can be evaluated without developing abstract models of their control-relevant aspects, and changes made to the networking code in simulations is guaranteed to be translated into production code without errors. A double-tank laboratory experimental setup controlled over a multi-hop relay wireless network is used to validate GISOO and demonstrate its features.

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Section: Related Workmentioning

confidence: 99%

“…8 Mhz microcontroller with 48 kB of Flash and 10 kB of RAM memory and a 250 kbps 2.GISOO environment, integrating COOJA (left) and…”

mentioning

confidence: 99%

GISOO: A virtual testbed for wireless cyber-physical systems

Aminian¹,

Araújo²,

Johansson³

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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“…It is widely used in the wireless networked control process of many applications [2–5]. The PID controller maintains the zone temperature to the desired level by adjusting the supply air temperature based on the control system error.…”

Section: Wsan System Modelsmentioning

confidence: 99%

“…Consequently, they can be widely adopted for many applications, including environmental monitoring and control, industrial machine condition, building automation, etc. In the building automation application [3–5], WSANs can be utilized to control and maintain the temperature inside buildings. Sensors gather the temperature in the zones of interest and send their signals to the controller.…”

Section: Introductionmentioning

confidence: 99%

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Energy Consumption and Control Response Evaluations of AODV Routing in WSANs for Building-Temperature Control

Booranawong

Teerapabkajorndet

Limsakul

2013

Sensors

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The main objective of this paper is to investigate the effects of routing protocols on wireless sensor and actuator networks (WSANs), focusing on the control system response and the energy consumption of nodes in a network. We demonstrate that routing algorithms designed without considering the relationship between communication and control cannot be appropriately used in wireless networked control applications. For this purpose, an ad-hoc on-demand distance vector (AODV) routing, an IEEE 802.15.4, and a building-temperature control system are employed for this exploration. The findings from our scenarios show that the AODV routing can select a path with a high traffic load for data transmission. It takes a long time before deciding to change a new route although it experiences the unsuccessful transmission of packets. As a result, the desirable control target cannot be achieved in time, and nodes consume more energy due to frequent packet collisions and retransmissions. Consequently, we propose a simple routing solution to alleviate these research problems by modifying the original AODV routing protocol. The delay-threshold is considered to avoid any congested connection during routing procedures. The simulation results demonstrate that our solution can be appropriately applied in WSANs. Both the energy consumption and the control system response are improved.

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