Learning-based model predictive control: Toward safe learning in control
Recent successes in the field of machine learning, as well as the availability of increased
sensing and computational capabilities in modern control systems, have led to a growing …
sensing and computational capabilities in modern control systems, have led to a growing …
Constrained model predictive control: Stability and optimality
Model predictive control is a form of control in which the current control action is obtained by
solving, at each sampling instant, a finite horizon open-loop optimal control problem, using …
solving, at each sampling instant, a finite horizon open-loop optimal control problem, using …
Efficient representation and approximation of model predictive control laws via deep learning
We show that artificial neural networks with rectifier units as activation functions can exactly
represent the piecewise affine function that results from the formulation of model predictive …
represent the piecewise affine function that results from the formulation of model predictive …
[HTML][HTML] Approximate model predictive building control via machine learning
Many studies have proven that the building sector can significantly benefit from replacing the
current practice rule-based controllers (RBC) by more advanced control strategies like …
current practice rule-based controllers (RBC) by more advanced control strategies like …
Approximating explicit model predictive control using constrained neural networks
This paper presents a method to compute an approximate explicit model predictive control
(MPC) law using neural networks. The optimal MPC control law for constrained linear …
(MPC) law using neural networks. The optimal MPC control law for constrained linear …
Learning an approximate model predictive controller with guarantees
A supervised learning framework is proposed to approximate a model predictive controller
(MPC) with reduced computational complexity and guarantees on stability and constraint …
(MPC) with reduced computational complexity and guarantees on stability and constraint …
[KİTAP][B] Constrained model predictive control
EF Camacho, C Bordons, EF Camacho, C Bordons - 2007 - Springer
The control problem was formulated in the previous chapters considering all signals to
possess an unlimited range. This is not very realistic because in practice all processes are …
possess an unlimited range. This is not very realistic because in practice all processes are …
Tutorial overview of model predictive control
JB Rawlings - IEEE control systems magazine, 2000 - ieeexplore.ieee.org
The paper provides a reasonably accessible and self-contained tutorial exposition on model
predictive control (MPC). It is aimed at readers with control expertise, particularly …
predictive control (MPC). It is aimed at readers with control expertise, particularly …
[KİTAP][B] Fuzzy modeling for control
R Babuška - 2012 - books.google.com
Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling
of partly-known nonlinear systems. Fuzzy models can effectively integrate information from …
of partly-known nonlinear systems. Fuzzy models can effectively integrate information from …
Deep learning-based long-horizon MPC: robust, high performing, and computationally efficient control for PMSM drives
M Abu-Ali, F Berkel, M Manderla… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
This article presents a computationally efficient and high performing approximate long-
horizon model predictive control (MPC) for permanent magnet synchronous motors …
horizon model predictive control (MPC) for permanent magnet synchronous motors …