Journal ArticleDOI
Handling uncertainty in economic nonlinear model predictive control: A comparative case study
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TLDR
In this paper, a multi-stage scenario-based nonlinear model predictive control (MPC) approach is proposed to deal with uncertainties in the context of economic NMPC, and a novel algorithm inspired by tube-based MPC is proposed in order to achieve a trade-off between the variability of the controlled system and the economic performance under uncertainty.About:
This article is published in Journal of Process Control.The article was published on 2014-08-01. It has received 142 citations till now. The article focuses on the topics: Model predictive control & Robust control.read more
Citations
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Economic Nonlinear Model Predictive Control
TL;DR: This survey provides a comprehensive overview of empc stability results: with and without terminal constraints, with andwithout dissipativtiy assumptions, with averaged constraints, formulations with multiple objectives and generalized terminal constraints as well as Lyapunov-based approaches.
Journal ArticleDOI
Rapid development of modular and sustainable nonlinear model predictive control solutions
TL;DR: In this paper, the authors propose a modularization of the NMPC implementations that facilitates the comparison of different solutions and the transition from simulation to online application, and the proposed platform supports the multi-stage robust NMPC approach to deal with uncertainty.
Journal ArticleDOI
Challenges in process optimization for new feedstocks and energy sources
Alexander Mitsos,Norbert Asprion,Christodoulos A. Floudas,Michael Bortz,Michael Baldea,Dominique Bonvin,Adrian Caspari,Pascal Schäfer +7 more
TL;DR: This manuscript focuses mainly on offline model-based optimization of design and operation, including the generation and selection of promising process alternatives for new feedstocks in conceptual design, multi-objective optimization, the estimation of thermodynamic parameters of new intermediates and the optimization of process operation under the volatile availability of the new feedstock and energy sources.
Journal ArticleDOI
Economic and Distributed Model Predictive Control: Recent Developments in Optimization-Based Control
TL;DR: In this paper, the authors give an overview of recent developments in the field of model predictive control and provide a brief introduction to the basic concepts and available stability results, as well as a brief overview of the available stability measures.
Journal ArticleDOI
A deep learning-based approach to robust nonlinear model predictive control
Sergio Lucia,Benjamin Karg +1 more
TL;DR: Empirical evidence is presented which shows that the use of deep neural networks with many hidden layers as opposed to shallow networks with only one significantly improves the learning process of a robust NMPC control law.
References
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Journal ArticleDOI
Survey Constrained model predictive control: Stability and optimality
TL;DR: This review focuses on model predictive control of constrained systems, both linear and nonlinear, and distill from an extensive literature essential principles that ensure stability to present a concise characterization of most of the model predictive controllers that have been proposed in the literature.
Journal ArticleDOI
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
TL;DR: A comprehensive description of the primal-dual interior-point algorithm with a filter line-search method for nonlinear programming is provided, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix.
Book
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
Andreas Griewank,Andrea Walther +1 more
TL;DR: This second edition has been updated and expanded to cover recent developments in applications and theory, including an elegant NP completeness argument by Uwe Naumann and a brief introduction to scarcity, a generalization of sparsity.
Journal ArticleDOI
SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers
Alan C. Hindmarsh,Peter Brown,K. E. Grant,Steven L. Lee,Radu Serban,Dan E. Shumaker,Carol S. Woodward +6 more
TL;DR: The current capabilities of the codes, along with some of the algorithms and heuristics used to achieve efficiency and robustness, are described.
Posted Content
Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers.
TL;DR: The SUNDIALS suite of nonlinear and DIfferential/ALgebraic equation solvers (SUNDIALs) as mentioned in this paper has been redesigned to better enable the use of application-specific and third-party algebraic solvers and data structures.