Mechatronics Control and Health Monitoring Lab
Event-triggered Control of Networked Control Systems
Networked control systems (NCS), wherein a communication network is used to close the feedback loop, the transmission of feedback signals and execution of the controller is currently carried out at periodic sampling instants. Thus, this scheme requires a significant computational power and network bandwidth. In contrast, the event-based aperiodic sampling and control, which is introduced recently, appears to relieve the computational burden and high network resource utilization. This research intended to develop event sampled adaptive regulation schemes in both discrete and continuous time domain for uncertain linear and nonlinear systems.
Optimization of the control policy in such a control paradigm is important from the performance point of view. In addition, optimization of the transmission/sampling intervals is equally important to save the resources. This research focuses on the both optimizing the sampling and control policy. From the application point of view, event-triggered control is most suitable for formation control of unmanned aerial vehicles, mobile robots, microgrids, and large scale systems.
Selected Publications
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A. Sahoo, Hao Xu, and S. Jagannathan, “Neural network–based event-triggered state feedback control of nonlinear continuous-time systems,” IEEE Transaction on Neural Networks and Learning Systems, vol. 27, no. 3, pp. 497-509, March 2016
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A. Sahoo, Hao Xu, and S. Jagannathan, “Adaptive near-optimal control of affine nonlinear continuous time systems by using event sampled neuro-dynamic programming," IEEE Transaction of Neural Network and Learning Systems, Feb, 2016, doi: 10.1109/TNNLS.2016.2539366.
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A. Sahoo, Hao Xu, and S. Jagannathan, “Adaptive neural network-based event-triggered control of single-input-single-output nonlinear discrete-time systems,” IEEE Transaction on Neural Networks and Learning Systems, vol. 27, no. 1, pp. 151-164, Jan. 2016.