Distributed Model Predictive Control and Optimization for Linear Systems With Global Constraints and Time-Varying Communication

نویسندگان

چکیده

In the article, we study distributed model predictive control (DMPC) problem for a network of linear discrete-time systems, where system dynamics are decoupled, constraints coupled, and communication networks described by time-varying directed graphs. A novel optimization algorithm called push-sum dual gradient (PSDG) is proposed to solve DMPC in fully way. We prove that sequences primal, variables converge their optimal values. Furthermore, implementation issues, stopping criteria designed allow early termination PSDG Algorithm, gossip-based check manner. It shown iteratively feasible, closed-loop exponentially stable. Finally, effectiveness approach verified via an example.

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ژورنال

عنوان ژورنال: IEEE Transactions on Automatic Control

سال: 2021

ISSN: ['0018-9286', '1558-2523', '2334-3303']

DOI: https://doi.org/10.1109/tac.2020.3021528