A physics-based digital twin for model predictive control of autonomous unmanned aerial vehicle landing
A McClellan, J Lorenzetti… - … Transactions of the …, 2022 - royalsocietypublishing.org
This paper proposes a two-level, data-driven, digital twin concept for the autonomous
landing of aircraft, under some assumptions. It features a digital twin instance (DTI) for model …
landing of aircraft, under some assumptions. It features a digital twin instance (DTI) for model …
Practical deployment of spectral submanifold reduction for optimal control of high-dimensional systems
Real-time optimal control of high-dimensional, nonlinear systems remains a challenging
task due to the computational intractability of their models. While several model-reduction …
task due to the computational intractability of their models. While several model-reduction …
Using spectral submanifolds for nonlinear periodic control
Very high dimensional nonlinear systems arise in many engineering problems due to semi-
discretization of the governing partial differential equations, eg through finite element …
discretization of the governing partial differential equations, eg through finite element …
Real-time three-level energy management strategy for series hybrid wheel loaders based on WG-MPC
R Gao, G Zhou, Q Wang - Energy, 2024 - Elsevier
Abstract The application of Hybrid Electric Wheel Loaders (HEWL) represents an attractive
option for future industrial development. In order to reduce the equivalent fuel consumption …
option for future industrial development. In order to reduce the equivalent fuel consumption …
Optimal Landing Control of eVTOL Vehicles Using ODE-Based Aerodynamic Model
View Video Presentation: https://doi. org/10.2514/6.2023-1742. vid In this paper, we propose
a novel approach to optimal landing control of electric vertical takeoff and landing (eVTOL) …
a novel approach to optimal landing control of electric vertical takeoff and landing (eVTOL) …
Stability and convergence of a randomized model predictive control strategy
DWM Veldman, A Borkowski… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
RBM-MPC is a computationally efficient variant of Model Predictive Control (MPC) in which
the Random Batch Method (RBM) is used to speed up the finite-horizon optimal control …
the Random Batch Method (RBM) is used to speed up the finite-horizon optimal control …
[HTML][HTML] Hierarchical higher-order dynamic mode decomposition for clustering and feature selection
This article introduces a novel, fully data-driven method for forming reduced order models
(ROMs) in complex flow databases that consist of a large number of variables. The algorithm …
(ROMs) in complex flow databases that consist of a large number of variables. The algorithm …
Tube-based robust MPC for two-timescale systems using reduced-order models
A tube-based robust Model Predictive Control (MPC) formulation is presented for systems
with slow and fast timescale dynamics. The controller uses a reduced-order model that …
with slow and fast timescale dynamics. The controller uses a reduced-order model that …
[HTML][HTML] Generalized Conditional Feedback System with Model Uncertainty
C Dai, Z Gao, Y Chen, D Li - Processes, 2023 - mdpi.com
Model uncertainty creates a largely open challenge for industrial process control, which
causes a trade-off between robustness and performance optimality. In such a case, we …
causes a trade-off between robustness and performance optimality. In such a case, we …
Finite-Dimensional RHC Control of Linear Time-Varying Parabolic PDEs: Stability Analysis and Model-Order Reduction
This chapter deals with the stabilization of a class of linear time-varying parabolic partial
differential equations employing receding horizon control (RHC). Here, RHC is finite …
differential equations employing receding horizon control (RHC). Here, RHC is finite …