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Distributed aperiodic model predictive control for multi-agent systems

Distributed aperiodic model predictive control for multi-agent systems

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In this study, the authors propose an aperiodic formulation of model predictive control for distributed agents with additive bounded disturbances. In the proposed method, each agent solves an optimal control problem only when certain control performances cannot be guaranteed according to certain triggering rules. This could lead to the reduction of energy consumption and the alleviation of over usage of communication resources. The triggering rules are derived for both event-triggered and self-triggered formulation. The authors proposed method is also verified through a simulation example.

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