Hybrid Aperiodic Control of Distributed Networked Nonlinear Systems

This paper proposes a hybrid aperiodic sampled-data control strategy for the stability of interconnected nonlinear systems. These interconnected nonlinear systems are modelled using Takagi-Sugeno fuzzy modelling technique. In the proposed methodology, first a self-triggering strategy is developed fo...

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Bibliographic Details
Main Authors: Bansal, Kritika, Mukhija, Pankaj
Format: Conference Proceeding
Language:English
Subjects:
distributed networked control systems (DNCS)
event-triggered control (ETC)
nonlinear systems
self-triggered control (STC)
T-S fuzzy
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Summary:This paper proposes a hybrid aperiodic sampled-data control strategy for the stability of interconnected nonlinear systems. These interconnected nonlinear systems are modelled using Takagi-Sugeno fuzzy modelling technique. In the proposed methodology, first a self-triggering strategy is developed for computing the next sampling instant for each node in a distributed networked control system. Further, an event-triggering condition is checked at these sampling instants and the control signal for each system is updated only if the event-triggering condition is satisfied. This reduces the number of sampling instants and number of times the control law is computed as compared to time-triggered mechanism and the aperiodic sampled-data strategy when applied alone. The results presented in this paper are validated through simulations and a comparison with other triggering mechanisms is also shown.
ISSN:2642-6102
DOI:10.1109/TENSYMP46218.2019.8971270