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Research about resilient sensor networks for power plant monitoring is recognized with Best Track Paper Award

The sensor network addressed in the paper assesses the operating conditions of a power plant. It is intended to measure process variables and assess plant status.| Short Read
EnlargeSemyon Meerkov
IMAGE:  Semyon Meerkov

Research involving the design of a resilient sensor network for use in a nuclear power plant was recognized at the 4th International Symposium on Resilient Control Systems as a Best Track Paper award. The paper, “Resilient Monitoring System: Design and Performance Analysis,” was authored by Humberto Garcia (Idaho National Laboratory), U-M students Naman Jhamaria and Heng Kuang, Wen-Chiao Lin (MSE PhD EE:Systems, Idaho National Laboratory), and Prof. Semyon M. Meerkov. Jhamaria and Kuang are U-M students working with Prof. Meerkov.

The paper is devoted to the design and performance analysis of an autonomous decentralized monitoring system (sensor network) that adapts to sensor malfunctioning and maintains the network performance at the best possible level.

The sensor network addressed in the paper assesses the operating conditions of a power plant. It is intended to measure process variables, e.g., temperature and pressure at various parts of the plant, and assess the plant status. Assuming that the sensors may malfunction (due to either natural or malicious causes), the network must be able to restructure itself, either by re-assigning some sensors or disregarding measurements produced by others, or both, so that the best possible plant status assessment is obtained.


Prof. Meerkov conducts research in Systems and Control, Production Systems Engineering, Communication Networks, Rational Behavior and Resilient Control Systems. He co-authored the book Production Systems Engineering with Jingshan Li in 2007, which after its third printing was revised and published in 2009. It is currently being translated into Chinese. He also co-authored the book Quasilinear Control: Performance Analysis and Design of Feedback Systems with Nonlinear Sensors and Actuators, published 2011.

Courses he has taught recently include EECS 460: Control Systems Analysis and Design, EECS 569: Production Systems Engineering, and EECS 662: Advanced Nonlinear Control.



Semyon Meerkov
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The outside of the Ford Robotics building

U-Michigan, Ford open world-class robotics complex

The facility will accelerate the future of advanced and more equitable robotics and mobility | Medium Read