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Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization
TLDR
Large-scale large-scale optimization solvers can be used to merge and replace the tasks of (steady-state) real-time optimization and (linear) model predictive control. Expand
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The advanced-step NMPC controller: Optimality, stability and robustness
TLDR
We propose the advanced-step NMPC controller based on nonlinear programming (NLP) sensitivity based on a simple reformulation of the NMPC problem. Expand
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A fast moving horizon estimation algorithm based on nonlinear programming sensitivity
Moving horizon estimation (MHE) is an efficient optimization-based strategy for state estimation. Despite the attractiveness of this method, its application in industrial settings has been ratherExpand
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Scalable stochastic optimization of complex energy systems
TLDR
We present a scalable approach and implementation for solving stochastic programming problems, with application to the optimization of complex energy systems under uncertainty. Expand
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Algorithmic innovations and software for the dual decomposition method applied to stochastic mixed-integer programs
TLDR
We present algorithmic innovations for the dual decomposition method to address two-stage stochastic programs with mixed-integer recourse and provide an open-source software implementation that can solve instances specified in C code, SMPS files, and Julia script. Expand
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Real-Time Nonlinear Optimization as a Generalized Equation
TLDR
We establish results for the problem of tracking a time-dependent manifold arising in real-time optimization by casting this as a parametric generalized equation. Expand
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Interior-point decomposition approaches for parallel solution of large-scale nonlinear parameter estimation problems
Multi-scenario optimization is a convenient way to formulate and solve multi-set parameter estimation problems that arise from errors-in-variables-measured (EVM) formulations. These large-scaleExpand
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Advanced step nonlinear model predictive control for air separation units
Cryogenic air separation units constitute an integral part of many industrial processes and next generation power plants. These units are characterized by fluctuating operating conditions to respondExpand
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Stability of multiobjective predictive control: A utopia-tracking approach
TLDR
We propose a utopia-tracking strategy to handle multiple conflicting objectives in model predictive control. Expand
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A Computational Framework for Uncertainty Quantification and Stochastic Optimization in Unit Commitment With Wind Power Generation
We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/economic dispatch formulations that account for windExpand
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