Event-Triggered Adaptive Neural Network Controller in a Cyber-Physical Framework

The importance of remotely placed controller in a cyber space with sensor-controller-actuator network has increased significantly in industrial, defense, and surveillance sector. Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant co...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2019-04, Vol.15 (4), p.2101-2111
Main Authors: Kar, Aniket K., Dhar, Narendra Kumar, Verma, Nishchal K.
Format: Article
Language:English
Subjects:
Actuators
Adaptive control
Adaptive neural network (NN) controller
Adaptive systems
Air conditioners
Air conditioning
Artificial neural networks
Automated guided vehicles
Case studies
Control systems design
Controllers
cyber–physical system
Data communication
Data transmission
Defense industry
delay
Delays
event-triggered controller
incremental PID controller
Internet
Neural networks
Path tracking
Proportional integral derivative
Remote control
Remote sensors
System dynamics
Uncertainty
Ventilation
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Summary:The importance of remotely placed controller in a cyber space with sensor-controller-actuator network has increased significantly in industrial, defense, and surveillance sector. Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant control signals and put unnecessary data on network. Therefore, an event-triggered adaptive controller that generates control action at required instants using state- and error-based conditions has been developed in this paper. A data transmission framework has also been designed in this paper that addresses network delay and packet losses. The proposed controller-communication methodology has been validated through two case studies, first, temperature tracking for heating ventilation and air conditioning system and, second, real-time path tracking by automated guided vehicle. The proposed methodology has also been duly compared with its time-triggered counterpart. The control updates are reduced to approximately 41% and 64% in the two case studies, respectively. The experimental results also prove the designed controller to be efficient when compared with event-triggered incremental PID controller using the same data transmission framework.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2861904