Accelerated gradient methods and dual decomposition in distributed model predictive control
TLDR
The evaluation shows that the proposed distributed optimization algorithm for mixed L"1/L"2-norm optimization based on accelerated gradient methods using dual decomposition can outperform current state-of-the-art optimization software CPLEX and MOSEK.About:
This article is published in Automatica.The article was published on 2013-03-01 and is currently open access. It has received 265 citations till now. The article focuses on the topics: Optimization problem & Duality (optimization).read more
Citations
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Journal ArticleDOI
Distributed Model Predictive Control with Event-Based Optimization
Ramin Rostami,Daniel Gorges +1 more
TL;DR: In this paper a novel event-based optimization algorithm is provided to reduce the number of communications in DMPC methods that are based on dual decomposition.
Journal ArticleDOI
Linear complementarity model predictive control with limited iterations for box-constrained problems
Isao Okawa,Kenichiro Nonaka +1 more
TL;DR: In this paper, a sufficient condition and its certification algorithm for solving box-constrained linear model predictive control (MPC) problems within a certain number of iterations equal to the number of constrained prediction points are presented.
Proceedings ArticleDOI
A distributed design of ℋ 2 suboptimal distributed controllers for networked systems
TL;DR: After solving the provided ℋ2 suboptimal control problem using distributed linear matrix inequalities (LMIs), each node can construct its own full-order sub-controller unit, which is implementable over the given network.
Journal ArticleDOI
Parallel MPC for Linear Systems With State and Input Constraints
TL;DR: In this article , a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints is proposed and the corresponding performance of the proposed method as well as the cost of the recursive feasibility guarantees is analyzed in the context of controlling a large-scale mechatronic system.
Journal ArticleDOI
Mitigation of communication failures in distributed model predictive control strategies
TL;DR: This paper addresses the problem of communication failures in DMPC strategies and proposes a distributed solution to cope with them in an information-exchange protocol that is based on distributed projection dynamics.
References
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Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
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A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Amir Beck,Marc Teboulle +1 more
TL;DR: A new fast iterative shrinkage-thresholding algorithm (FISTA) which preserves the computational simplicity of ISTA but with a global rate of convergence which is proven to be significantly better, both theoretically and practically.
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Introductory Lectures on Convex Optimization: A Basic Course
TL;DR: A polynomial-time interior-point method for linear optimization was proposed in this paper, where the complexity bound was not only in its complexity, but also in the theoretical pre- diction of its high efficiency was supported by excellent computational results.
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Smooth minimization of non-smooth functions
TL;DR: A new approach for constructing efficient schemes for non-smooth convex optimization is proposed, based on a special smoothing technique, which can be applied to functions with explicit max-structure, and can be considered as an alternative to black-box minimization.