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Nonlinear Model Predictive Control
2021The nonlinear model predictive control (NMPC) approach allows more challenging control problems to be handled than those dealt with by the linear model predictive control (LMPC) method. For engine control problems, the consideration of their nonlinear process behavior is particularly important as their treatment as a linearized system is often not ...
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Nonlinear model predictive control of a cutting process
Neurocomputing, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Primoz Potocnik, Igor Grabec
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Nonlinear Model Predictive Control
2018This chapter presents a model-based strategy for a PHEV with the use of MPC concept. MPC appears to be an appropriate scheme to utilize contemporary concept potentials and to satisfy the automotive requisites, as most can be defined in the form of a constrained multi-input, multi-output optimal control problem, and MPC provides approximate resolution ...
Amir Taghavipour +2 more
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Model Predictive Control with Internal Model for Nonlinear Systems
IFAC Proceedings Volumes, 2001Abstract In the last years an important research effort has been made to obtain stabilizing state-feedback MPC control law with guaranteed stability for nonlinear systems, so that a relatively mature stage has just now been reached. In spite of these recent developments, for the tracking problem with guaranteed stability properties only few ...
L. Magni, SCATTOLINI, RICCARDO
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Nonlinear model predictive control of a GDI engine
2001 European Control Conference (ECC), 2001A model predictive approach to the control of a GDI engine is presented. Fuzzy Takagi-Sugeno type models are used to predict the future engine behaviour. The optimization algorithm is based on instantaneous linearization of the nonlinear prediction model at the current operating point.
Stanimir Mollov +2 more
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Nonlinear model predictive control
Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), 1999Nonlinear model predictive control (NMPC) has been introduced in commercial applications. Since mid 1996 approximately 50 applications have been commissioned in polymers, chemicals, food, pulp and paper, and oil refining. This industrial presentation provides a brief overview of the commercial NMPC package and presents a summary of a specific polymers ...
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Nonlinear offset-free model predictive control
Automatica, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Manfred Morari, Urban Maeder
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Nonlinear Model Predictive Control
2012A nonlinear model predictive control (NMPC) strategy requires the formulation of an optimization problem. For online NMPC the nonlinear programming problem must be solved numerically at every sampling interval, while explicit NMPC assumes that an explicit representation of the solution can be computed using multi-parametric nonlinear programming.
Alexandra Grancharova, Tor Arne Johansen
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Wiener model based nonlinear predictive control
International Journal of Systems Science, 2000This paper addresses the problem of discrete-time nonlinear predictive control of W iener systems. Wiener-model-based nonlinear predictive control combines the advantages of linear-model-based predictive control and gain scheduling while retaining a moderate level of computational complexity.
Samo Gerksic +3 more
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Nonlinear Model Predictive Control: Control and Prediction Horizon
IFAC Proceedings Volumes, 2000Abstract In this paper a new class of Model Predictive control algorithms for nonlinear systems is introduced. A prediction horizon longer than the control horizon is used. It is shown that in this way it is possible to enlarge the domain of attraction and to improve the performance without enlarging the dimension of the optimization space.
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