DISTRIBUTED CONSENSUS-BASED CALIBRATION OF NETWORKED CONTROL SYSTEMS

Maja Stanković, Dragan Antić

DOI Number
https://doi.org/10.22190/FUACR1902095S
First page
095
Last page
111

Abstract


In this paper a new algorithm for distributed blind macro-calibration of Networked Control Systems is presented. It is assumed that the measured signal is stochastic and unknown. The algorithm is in the form of recursions of gradient type for estimation of the correction parameters for sensor gains and offsets. The recursion for gain correction is autonomous, derived from the measurement increments. The recursion for offset correction is based on differences between local measurements and utilizes the results of gain correction. It is proved that the algorithm provides asymptotic convergence to consensus in the sense that the corrected gains and offsets are equal for all sensors. It is demonstrated that the adopted structure of the algorithm enables obtaining high convergence rate, superior to the algorithms existing in the literature. Simulation results are provided illustrating the proposed algorithm properties.

Keywords

networked control systems, blind macro-calibration, sensor, actuator networks, distributed gradient algorithms, consensus

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References


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DOI: https://doi.org/10.22190/FUACR1902095S

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