Dissipativity-Guaranteed Distributed Model Predictive Controller for Reconfigurable Large-Scale System

You, He; Li, Shaoyuan

doi:10.1007/s00034-019-01257-0

Cited by 5 publications

(1 citation statement)

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“…Dissipativity property, 12,13 as the common feature of PFSs that are governed by principles of physical energy conservation and dissipation, has been widely utilized in system analysis 14 and control design 15‐17 . Dissipativity‐based control has been applied to a variety of PFSs in centralized, 18‐20 decentralized, and distributed control architecture 2,21‐23 . The classical control algorithm requires that dissipativity condition holds only for a particular equilibrium, while incremental dissipativity 24,25 and differential dissipativity, 26,27 as extensions of the conventional dissipativity property, require that a dissipation inequality holds along any two arbitrary trajectories of a forced system.…”

Section: Introductionmentioning

confidence: 99%

A dissipativity‐based model predictive control algorithm for power flow systems with equilibrium‐independent stability guaranteed

You

2020

Intl J Robust & Nonlinear

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This article presents a distributed model predictive control algorithm for power flow systems that can maintain overall stability when the system equilibrium configuration changes. The dynamics of the large‐scale power flow systems can be described by transportation, conversion, and storage of energy among and across subsystems. By strategically choosing the output for each subsystem and augmenting each local model predictive controller with a special passivity‐incremental constraint, the equilibrium‐independent dissipativity property of each closed‐loop subsystem can be guaranteed. The dissipativity‐preserving coupling between subsystems in the power flow system can be utilized to maintain equilibrium‐independent dissipativity and stability of the overall system. Simulation results of a fluid tank system with a changing equilibrium configuration show the effectiveness of the proposed algorithm.

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