Results 141 to 150 of about 1,367 (181)

Fast NMPC schemes for regulatory and economic NMPC – A review

Journal of Process Control, 2016
Abstract In this paper, NMPC schemes based on fast update methods (fast NMPC schemes) are reviewed that strive to provide a fast but typically suboptimal update of the control variables at each sampling instant with negligible computational delay. The review focuses on schemes that employ one of two subclasses of fast update methods developed for ...
Wolfgang Marquardt
exaly   +2 more sources

Volterra-Laguerre modeling for NMPC

2007 9th International Symposium on Signal Processing and Its Applications, 2007
Volterra series are perhaps the best understood nonlinear system representations in signal processing. They can be used to model a wide class of nonlinear systems. However, since these models are non-parsimonious in parameters, the symmetric kernel parameters are used. This model is used to evaluate identification of a pH-neutralization process.
Sanaz Mahmoodi, Allahyar Montazeri, Javad Poshtan, MohammadReza Jahed-Motlagh, Majid Poshtan   +4 more
openaire   +1 more source

Data-Driven Economic NMPC Using Reinforcement Learning [PDF]

IEEE Transactions on Automatic Control, 2020
Reinforcement Learning (RL) is a powerful tool to perform data-driven optimal control without relying on a model of the system. However, RL struggles to provide hard guarantees on the behavior of the resulting control scheme. In contrast, Nonlinear Model Predictive Control (NMPC) and Economic NMPC (ENMPC) are standard tools for the closed-loop optimal ...
Sébastien Gros, Mario Zanon
exaly   +3 more sources

On stability of multiobjective NMPC with objective prioritization

Automatica, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Defeng He, Lei Wang, Jing Sun 0003
openaire   +2 more sources

Adaptive Volterra-Laguerre modelling for NMPC

2007 9th International Symposium on Signal Processing and Its Applications, 2007
Model predictive control (MPC) is one of the most successful controllers in process industries. Process industries need a predictive controller that is low cost, easy to setup and maintains an adaptive behavior which accounts for plant changes, nonlinearities and under-modeling.
Allahyar Montazeri, Sanaz Mahmoodi, Javad Poshtan, Majid Poshtan, MohammadReza Jahed-Motlagh   +4 more
openaire   +1 more source

Exact turnpike properties and economic NMPC

European Journal of Control, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Timm Faulwasser, Dominique Bonvin
openaire   +2 more sources

Fast NMPC: A reality-steered paradigm: Key properties of fast NMPC algorithms

2014 European Control Conference (ECC), 2014
In this paper, the paradigm of fast Nonlinear Model Predictive Control is recalled. Then a fundamental inequality that conditions the closed-loop stability is derived. Based on this inequality, it is shown that the comparison between different algorithms in the context of Fast NMPC must be based not only on the efficiency per iteration but also on the ...
openaire   +1 more source

Explicit Stochastic NMPC

2012
This chapter considers two approaches to explicit stochastic NMPC of general constrained nonlinear discrete-time systems in the presence of disturbances and/or parameter uncertainties with known probability distributions. In Section 7.2, an approach to explicit solution of closed-loop (feedback) stochastic NMPC problems for constrained nonlinear ...
Alexandra Grancharova, Tor Arne Johansen
openaire   +1 more source

Framework in PYOMO for the assessment and implementation of (as)NMPC controllers

Computers & Chemical Engineering, 2016
Abstract Model predictive control (MPC) is an advanced control strategy that has a growing interest for research and applications because of its good performance in many kind of processes and its ability to handle constraints, perform optimization, and consider economic aspects and nonlinearities of the process.
Federico Lozano Santamaría, Jorge Mario Gómez   +1 more
openaire   +1 more source

Dual decomposition for QPs in scenario tree NMPC

2015 European Control Conference (ECC), 2015
In the field of nonlinear model predictive control (NMPC) under uncertainty we use a robustification approach based on a scenario tree formulation. This approach is known to be less conservative than worst-case approaches. A main challenge of scenario tree NMPC in high-dimensional uncertainty spaces is the exponential growth of the number of scenarios ...
Conrad Leidereiter, Andreas Potschka, Hans Georg Bock   +2 more
openaire   +1 more source