• Journal of Power Electronics
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• v.17 no.6
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• pp.1650-1657
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• 2017

In this study, the distributed secondary voltage control of islanded microgrids with multi-agent consensus algorithm is investigated. As an alternative to a time-triggered approach, an event-triggered scheme is proposed to reduce the communication load among inverter-based distributed generators (DGs). The proposed aperiodic control scheme reduced unnecessary utilization of limited network bandwidth without degrading control performance. By properly establishing a distributed triggering condition in DG local controller, each inverter is only required to send voltage information when its own event occurs. The compensation of voltage amplitude deviation can be realized, and redundant data exchange related to fixed high sampling rate can be avoided. Therefore, an efficient use of communication infrastructure can be realized, particularly when the system is operating in steady state. The effectiveness of the proposed scheme is verified by simulations on a microgrid test system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.168-169
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• 2022

In this study, we investigates the auto-berthing problem for the underactuated surface vessel in the presence of constraints of dynamic uncertainties, finite time, transmission load, and environmental disturbance. A novel control scheme is proposed by fusing the finite time control technology and the event-triggered input algorithm. In the algorithm, differential homeomorphism coordinate the transformation is used to solve the problem of underactuation. Then, we apply the finite time technology and event triggered to save the time of the berthing vessel and relieve transmission burden between the controller and the vessel respectively. Moreover, a radial basis function network is used to approximate unknown nonlinear functions, and minimum learning parameters are introduced to lessen the computational complexity. A sufficient effort has been made to verify the stability of the closed-loop system based on the Lyapunov stability theory. Finally, simulation results display the effectiveness of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.165-170
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• 2017

This paper presents an event-triggered model predictive controller for adaptive cruise control system with sampled and quantized-data. Unlike existing works, a longitudinal continuous-time model is used for the predictive control of the system. To efficiently utilize network resources, event-trigger scheme is employed, which allows limited sensor and actuator signal satisfying the condition that the measurement of errors is over the ratio of a trigger level. The proposed control gain is obtained by solving a convex problem satisfying several linear matrix inequalities at every sampling times. Simulation results are given to show the effectiveness of the proposed design method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1229-1233
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• 2010

In event-driven wireless sensor networks, network congestion occurs when event data, which have higher transmission rates than periodic sensing data, arc forwarded to bottleneck links. As the congestion continues, congestion collapse is triggered, so most of packets from source nodes are failed to transmit to a sink node. Rate control schemes can be a solution for preventing the congestion collapse problem. In this paper, a rate control scheme that each node controls child node's data rate based on congestion patterns is proposed. Experiments show that the proposed scheme effectively controls network congestion and successfully transmits more event data packets to a sink node than existing rate control schemes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1291-1293
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• 2007

Due to dense deployment and innumerable amount of traffic flow in wireless sensor networks (WSNs), congestion becomes more common phenomenon from simple periodic traffic to unpredictable bursts of messages triggered by external events. Even for simple network topology and periodic traffic, congestion is a likely event due to dynamically time varying wireless channel condition and contention caused due to interference by concurrent transmissions. In this paper, we have proposed three mechanisms: upstream source count and buffer based rate control and snoop based MAC level ACK scheme to avoid congestion. The simulation results show that our proposed mechanism achieves around 80% delivery ratio even under bursty traffic condition