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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Proceedings ArticleDOI
Approximated stochastic model predictive control using statistical linearization of nonlinear dynamical system in latent space
TL;DR: This paper introduces a novel data-driven approach to approximately linearize a nonlinear dynamical system in a latent space, and then identifies a stochastic linearized system using a subspace state space system identification algorithm.
Book ChapterDOI
Distributed Robust Model Predictive Control of Interconnected Polytopic Systems
TL;DR: In this article, a suboptimal approach to distributed robust MPC for uncertain systems consisting of polytopic subsystems with coupled dynamics subject to both state and input constraints is proposed, defined in terms of the optimization of a cost function accumulated over the uncertainty and satisfying state constraints for a finite subset of uncertainties.
Journal ArticleDOI
A multi-step robust model predictive control scheme for polytopic uncertain multi-input systems
TL;DR: In this paper, a control scheme known as multi-step robust MPC is presented for polytopic uncertain multi-input systems, where only one or several state feedback laws are optimized at each time interval to reduce computational complexity.
Journal ArticleDOI
Fair Virtual Energy Storage System Operation for Smart Energy Communities
TL;DR: In this paper , the authors proposed a fair virtual energy storage operation method for smart energy communities that involve groups of energy consumption units, where the cost and resource fairness indices are defined as the benefit and VESS usage proportional to the investment cost, respectively.
Proceedings ArticleDOI
Distributed Linear Quadratic Regulator for the Synthesis of a Separable Terminal Cost for Distributed Model Predictive Control
TL;DR: This paper presents an alternative suboptimal design providing both a stabilizing terminal cost function which preserves the network structure and a nominal distributed control law for the unconstrained system is presented.
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.
Journal ArticleDOI
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.
Book
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.
Journal ArticleDOI
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.