Ramp-net: A robust adaptive mpc for quadrotors via physics-informed neural network
Model Predictive Control (MPC) is a state-of-the-art (SOTA) control technique which requires
solving hard constrained optimization problems iteratively. For uncertain dynamics …
solving hard constrained optimization problems iteratively. For uncertain dynamics …
Eingebettete Optimierung in der Regelungstechnik–Grundlagen und Herausforderungen
R Findeisen, K Graichen… - at …, 2018 - degruyter.com
Die effiziente Lösung von Optimierungsproblemen in Echtzeit bildet die Grundlage vieler
moderner Regelungs-und Schätzverfahren. So basieren die prädiktive Regelung sowie die …
moderner Regelungs-und Schätzverfahren. So basieren die prädiktive Regelung sowie die …
A new Takagi-Sugeno-Kang model-based stabilizing explicit MPC formulation: an experimental case study with implementation embedded in a PLC
TPG Mendes, L Schnitman… - Expert Systems with …, 2022 - Elsevier
This manuscript presents a new fuzzy approach applied to Model Predictive Control (MPC).
We propose to re-interpret the table of IF-THEN rules from an explicit MPC solution as an …
We propose to re-interpret the table of IF-THEN rules from an explicit MPC solution as an …
Parallel MPC for linear systems with input constraints
This article is about a real-time model predictive control algorithm for large-scale, structured
linear systems with polytopic control constraints. The proposed controller receives the …
linear systems with polytopic control constraints. The proposed controller receives the …
Distributed optimization and control with ALADIN
This chapter aims to give a concise overview of distributed optimization and control
algorithms based on the augmented Lagrangian based alternating direction inexact Newton …
algorithms based on the augmented Lagrangian based alternating direction inexact Newton …
Research on model predictive control of autonomous underwater vehicle based on physics informed neural network modeling
T Liu, J Zhao, J Huang, Z Li, L Xu, B Zhao - Ocean Engineering, 2024 - Elsevier
In the rapidly evolving field of Autonomous Underwater Vehicles (AUVs), achieving precise
control remains a critical endeavor. This study presents a pioneering integration of Model …
control remains a critical endeavor. This study presents a pioneering integration of Model …
Effective GPU parallelization of distributed and localized model predictive control
To effectively control large-scale distributed systems online, model predictive control (MPC)
has to swiftly solve the underlying high-dimensional optimization. There are multiple …
has to swiftly solve the underlying high-dimensional optimization. There are multiple …
Revisiting reachability-driven explicit MPC for embedded control
The real-time implementation of the explicit MPC suffers from the evaluation of the,
potentially large, lookup table. The paper revisits the original approach and presents an …
potentially large, lookup table. The paper revisits the original approach and presents an …
Complexity reduction of explicit MPC based on fuzzy reshaped polyhedrons for use in industrial controllers
The explicit model predictive control (EMPC) generates the rules of control defined for a set
of polyhedral regions. Online EMPC calculations consist of searching a look-up table to find …
of polyhedral regions. Online EMPC calculations consist of searching a look-up table to find …
Design and implementation of a sub-optimal explicit mpc using a novel complexity reduction approach based on fuzzy reshaped active regions
Abstract The Explicit Model Predictive Control (EMPC) has emerged as a powerful
technique to solve the optimization problem for embedded applications. Despite practical …
technique to solve the optimization problem for embedded applications. Despite practical …