Economic stochastic model predictive control using the unscented kalman filter
Economic model predictive control is a popular method to maximize the efficiency of a
dynamic system. Often, however, uncertainties are present, which can lead to lower …
dynamic system. Often, however, uncertainties are present, which can lead to lower …
Stochastic nonlinear model predictive control using Gaussian processes
Model predictive control is a popular control approach for multivariable systems with
important process constraints. The presence of significant stochastic uncertainties can …
important process constraints. The presence of significant stochastic uncertainties can …
[PDF][PDF] Combining Gaussian processes and polynomial chaos expansions for stochastic nonlinear model predictive control
Abstract Model predictive control is an advanced control approach for multivariable systems
with constraints, which is reliant on an accurate dynamic model. Most real dynamic models …
with constraints, which is reliant on an accurate dynamic model. Most real dynamic models …
Economic stochastic nonlinear model predictive control of a semi-batch polymerization reaction
Batch processes are ubiquitous in the chemical industry and difficult to control, such that
nonlinear model predictive control is one of the few promising control techniques. Many …
nonlinear model predictive control is one of the few promising control techniques. Many …
Output feedback stochastic nonlinear model predictive control of a polymerization batch process
Nonlinear model predictive control (NMPC) is one of the few methods that can handle
multivariate nonlinear control problems while accounting for process constraints. Many …
multivariate nonlinear control problems while accounting for process constraints. Many …
Constrained tracking control of stochastic multivariable nonlinear systems using unscented Kalman filter
To overcome the challenges, including propagation of the stochastic uncertainties through a
nonlinear model and full determination of the states over the prediction horizon for …
nonlinear model and full determination of the states over the prediction horizon for …
Constrained tracking control of stochastic multivariable nonlinear systems via Gaussian process predictions
To overcome the difficulty of propagating the stochastic uncertainties through a nonlinear
model for successful online implementation of the stochastic nonlinear model predictive …
model for successful online implementation of the stochastic nonlinear model predictive …
A model‐and data‐driven predictive control approach for tracking of stochastic nonlinear systems using Gaussian processes
Nonlinear model predictive control (NMPC) is one of the few control methods that can
handle complex nonlinear systems with multi‐objectives and various constraints. However …
handle complex nonlinear systems with multi‐objectives and various constraints. However …
Operación y control de sistemas comunitarios de almacenamiento de energía en redes de distribución aéreas
HJ Yepes Fernández - 2022 - manglar.uninorte.edu.co
La presente tesis propone el análisis de la posible integración de los Sistemas
Comunitarios de Almacenamiento de Energía en las redes eléctricas de distribución en …
Comunitarios de Almacenamiento de Energía en las redes eléctricas de distribución en …
Stochastic nonlinear model predictive control of a batch fermentation process
Nonlinear model predictive control (NMPC) is an attractive control approach to regulate
batch processes reliant on an accurate dynamic model. Most dynamic models however are …
batch processes reliant on an accurate dynamic model. Most dynamic models however are …