8 research outputs found
DISTRIBUTED CONSENSUS-BASED CALIBRATION OF NETWORKED CONTROL SYSTEMS
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
Periodic event-triggered output regulation for linear multi-agent systems
This study considers the problem of periodic event-triggered (PET)
cooperative output regulation for a class of linear multi-agent systems. The
advantage of the PET output regulation is that the data transmission and
triggered condition are only needed to be monitored at discrete sampling
instants. It is assumed that only a small number of agents can have access to
the system matrix and states of the leader. Meanwhile, the PET mechanism is
considered not only in the communication between various agents, but also in
the sensor-to-controller and controller-to-actuator transmission channels for
each agent. The above problem set-up will bring some challenges to the
controller design and stability analysis. Based on a novel PET distributed
observer, a PET dynamic output feedback control method is developed for each
follower. Compared with the existing works, our method can naturally exclude
the Zeno behavior, and the inter-event time becomes multiples of the sampling
period. Furthermore, for every follower, the minimum inter-event time can be
determined \textit{a prior}, and computed directly without the knowledge of the
leader information. An example is given to verify and illustrate the
effectiveness of the new design scheme.Comment: 17 pages, 13 figures, submitted to Automatica. accepte