Journal Article10.1016/S1474-6670(17)31930-4
Sensitivity-Based Solution Updates in Closed-Loop Dynamic Optimization
J.V. Kadam,Wolfgang Marquardt +1 more
71
TL;DR: A novel approach for closed-loop optimization is presented that systematically combines a fast update strategy with rigorous optimization when necessary that is very effective to handle uncertainty while requiring only a minimum number of full realtime optimizations reducing the on-line computational expense.
read more
About: This article is published in IFAC Proceedings Volumes. The article was published on 01 Jul 2004. The article focuses on the topics: Probabilistic-based design optimization & Sensitivity (control systems).
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
The advanced-step NMPC controller: Optimality, stability and robustness
TL;DR: This study extends the concept of first-principles models for nonlinear model predictive control through a simple reformulation of the NMPC problem and proposes the advanced-step NMPC controller, which enjoys the same nominal stability properties of the conventionalNMPC controller without computational delay.
447
Real-Time Model Predictive Control for Shipboard Power Management Using the IPA-SQP Approach
Hyeongjun Park,Jing Sun,Steven D. Pekarek,Philip Stone,Daniel F. Opila,Richard T. Meyer,Ilya Kolmanovsky,Raymond A. DeCarlo +7 more
TL;DR: Simulations and experiments show that real-time optimization, constraint enforcement, and fast load following can be achieved with the IPA-SQP algorithm.
117
Integration of Economical Optimization and Control for Intentionally Transient Process Operation
J.V. Kadam,Wolfgang Marquardt +1 more
TL;DR: In this paper, a decomposition strategy is presented to separate economical and control objectives by formulating two subproblems in closed-loop, model-based and model-free at the implementation level.
117
Fast economic model predictive control based on NLP-sensitivities
TL;DR: In this article, sufficient conditions for nominal stability are derived for NMPC controllers that incorporate economic stage costs with appropriate regularization, and a constructive strategy to calculate the regularization term directly is derived.
98
Neighboring-extremal updates for nonlinear model-predictive control and dynamic real-time optimization
TL;DR: Kadam et al. as mentioned in this paper proposed a method for solving dynamic optimization problems based on neighboring-extremal updates suitable for applications in nonlinear model-predictive control and dynamic real-time optimization.
95
References
Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations
Moritz Diehl,H. Georg Bock,Johannes P. Schlöder,Rolf Findeisen,Zoltan K. Nagy,Frank Allgöwer +5 more
TL;DR: In this paper, the authors present a model predictive control (NMPC) for a high-purity distillation column subject to parameter disturbances, which is based on the direct multiple-shooting (DMS) method.
717
Online optimization of large scale systems
Martin Grötschel,Sven O. Krumke,Jörg Rambau +2 more
- 01 Jan 2001
TL;DR: In this article, real-time control of a container crane under state-dependent constraints using nonlinear nonlinear programming (NLP) and sensitivity analysis is used to find the optimal control solution for the nonlinear heat equation.
On Converting Optimal Control Problems into Nonlinear Programming Problems
Dieter Kraft
- 01 Jan 1985
TL;DR: Two discretization schemes are proposed which are based on the parameterization of the control functions and on the parameters of the state functions, leading to direct shooting and direct collocation algorithms, respectively.
221
A Two-Level Strategy of Integrated Dynamic Optimization and Control of Industrial Processes—a Case Study
J.V. Kadam,Martin Schlegel,Wolfgang Marquardt,R.L. Tousain,D.H. van Hessem,J. van den Berg,O.H. Bosgra +6 more
TL;DR: In this article, a two-level strategy integrating dynamic trajectory optimization and control for the operation of chemical processes is discussed, where the benefit of online dynamic re-optimization of operational trajectories in case of disturbances is illustrated by a case study on a semi-batch reactive distillation process producing methyl acetate.