Journal ArticleDOI
Multi-stage nonlinear model predictive control applied to a semi-batch polymerization reactor under uncertainty
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TLDR
In this paper, the authors present a robust non-conservative nonlinear model predictive control (MPC) approach based on the representation of the evolution of the uncertainty by a scenario tree, and leads to a non-ervative robust control of the uncertain plant because the adaptation of future inputs to new information is taken into account.About:
This article is published in Journal of Process Control.The article was published on 2013-10-01. It has received 291 citations till now. The article focuses on the topics: Model predictive control & Robust control.read more
Citations
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Journal ArticleDOI
Robust control of a supermarket refrigeration system using multi-stage NMPC
TL;DR: In this article, the authors study the application of nonlinear model predictive control (NMPC) to a supermarket refrigeration system under uncertainty and show that the presence of uncertainties in the model leads to constraint violations when standard NMPC is applied.
Proceedings ArticleDOI
Resilient Control of Interconnected Microgrids Under Attack by Robust Nonlinear MPC
TL;DR: In this paper , the authors introduce a mathematical model for interconnected, physically coupled microgrids with renewable generation that are exposed to the risk of attacks and present a resilient framework that combines a model-based method to identify occurring attacks and a model predictive control scheme to compute robust control inputs.
Journal ArticleDOI
Evaluation of Different Control Strategies for Trajectory Following of a Robotic Capsule Endoscope Under Rotating Magnetic Actuation
TL;DR: In this paper , the authors investigated the trajectory following problem of a robotic capsule under rotating magnetic actuation, in order to realize efficient and accurate navigation of the capsule in the narrow, complex intestinal environments.
Journal ArticleDOI
A Hybrid Neural Network Approach for Adaptive Scenario-Based Model Predictive Control in the LPV Framework
TL;DR: In this article , a hybrid neural network (NN) approach for adaptive scenario-based model predictive control (SMPC) design of nonlinear systems in the linear parameter-varying (LPV) framework is presented.
Journal ArticleDOI
Dual-control based approach to batch process operation under uncertainty based on optimality-conditions parameterization.
Radoslav Paulen,Miroslav Fikar +1 more
TL;DR: In this paper, a scheme for dual robust control of batch processes under parametric uncertainty is presented, which uses parametrized conditions of optimality in the adaptive predictive-control fashion.
References
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Journal ArticleDOI
Model predictive control: theory and practice—a survey
TL;DR: The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-, 2-, and ∞-norm formulations of the performance objective are discussed.
Journal ArticleDOI
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
TL;DR: An SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility in the original problem and the QP subproblems is discussed and a reduced-Hessian semidefinite QP solver (SQOPT) is discussed.
Journal ArticleDOI
Robust model predictive control of constrained linear systems with bounded disturbances
TL;DR: This paper provides a novel solution to the problem of robust model predictive control of constrained, linear, discrete-time systems in the presence of bounded disturbances by solving the optimal control problem that is solved online.
Journal ArticleDOI
A Multiple Shooting Algorithm for Direct Solution of Optimal Control Problems
Hans Georg Bock,K.J. Plitt +1 more
TL;DR: A condensing algorithm for the solution of the approximating linearly constrained quadratic subproblems, and high rank update procedures are introduced, which are especially suited for optimal control problems and lead to significant improvements of the convergence behaviour and reductions of computing time and storage requirements.
Journal ArticleDOI
Scenarios and policy aggregation in optimization under uncertainty
TL;DR: This paper develops for the first time a rigorous algorithmic procedure for determining a robust decision policy in response to any weighting of the scenarios.