Distributed Model Predictive Control for Linear Systems With Adaptive Terminal Sets


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Date

2020-03

Publication Type

Journal Article

ETH Bibliography

yes

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Abstract

We propose a distributed model predictive control scheme for linear time-invariant constrained systems that admit a separable structure. To exploit the merits of distributed computation algorithms, the terminal cost and invariant terminal set of the optimal control problem need to respect the coupling structure of the system. Existing methods to address this issue typically separate the synthesis of terminal controllers and costs from the one of terminal sets, and do not explicitly consider the effect of the current and predicted system states on this synthesis process. These limitations can adversely affect performance due to small or even empty terminal sets. Here, we present a unified framework to encapsulate the synthesis of both the stabilizing terminal controller and invariant terminal set into the same optimization problem. Conditions for Lyapunov stability and invariance are imposed in the synthesis problem in a way that allows the terminal cost and invariant terminal set to admit the desired distributed structure. We illustrate the effectiveness of the proposed method on several numerical examples.

Publication status

published

Editor

Book title

Volume

65 (3)

Pages / Article No.

1044 - 1056

Publisher

IEEE

Event

Edition / version

Methods

Software

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Subject

Cooperative control; Large-scale systems; Optimal control; Predictive control; Robust adaptive control

Organisational unit

03751 - Lygeros, John / Lygeros, John check_circle

Notes

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