Holistic Control and Management of Industrial Wireless Processes
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Wireless sensor actuator networks (WSANs) are gaining rapid adoption in industrial automation and manufacturing due to their low deployment cost and flexibility.
While early success of industrial WSANs focused on monitoring applications, there are significant advantages, and also challenges, in employing WSANs in feedback control applications, since they require careful design and testing of both network configurations as well as control algorithms.
We propose to create a holistic controller and network manager for wireless process control systems capable of predicting and adapting to changing cyber-physical conditions.
In this new framework, the controller, using a prediction model of the plant, estimates and compares the performance loss associated to different network configurations.
Accordingly, the network manager adapts network configurations to optimize the control performance as requested by the controller.
Our proposed feedback configuration between holistic controller and network manager will enable industrial process control applications that are resilient against disturbances to both the physical plant and the wireless network.
We will validate our results using wireless hardware measurements from our testbeds, and our collaboration with Emerson Electric Co. will provide feedback regarding realistic industrial settings and commercialization potential of our solutions.
Submitted by Humberto Gonzalez
on
Wireless sensor actuator networks (WSANs) are gaining rapid adoption in industrial automation and manufacturing due to their low deployment cost and flexibility.
While early success of industrial WSANs focused on monitoring applications, there are significant advantages, and also challenges, in employing WSANs in feedback control applications, since they require careful design and testing of both network configurations as well as control algorithms.
We propose to create a holistic controller and network manager for wireless process control systems capable of predicting and adapting to changing cyber-physical conditions.
In this new framework, the controller, using a prediction model of the plant, estimates and compares the performance loss associated to different network configurations.
Accordingly, the network manager adapts network configurations to optimize the control performance as requested by the controller.
Our proposed feedback configuration between holistic controller and network manager will enable industrial process control applications that are resilient against disturbances to both the physical plant and the wireless network.
We will validate our results using wireless hardware measurements from our testbeds, and our collaboration with Emerson Electric Co. will provide feedback regarding realistic industrial settings and commercialization potential of our solutions.