In this paper, proper orthogonal decomposition method is employed to build a reduced-order model from a high-order nonlinear permanent magnet synchronous machine model with multiple inputs. Three parameters are selected as the multiple inputs of the machine. These parameters are terminal current, angle of the terminal current, and rotation angle. To produce the lower-rank system, snapshots or instantaneous system states are projected onto a set of orthonormal basis functions with small dimension. The reduced model is then validated by comparing the vector potential, flux density distribution, and torque results of the original model,which indicates the capability of using the proper orthogonal decomposition method in the multi-variable inpu...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
This chapter contains three advanced topics in model order reduction (MOR): nonlinear MOR, MOR for m...
Electrical circuits usually contain nonlinear components. Hence we are interested in MOR methods tha...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
In this paper, proper orthogonal decomposition (POD) method is employed to build a reduced-order mod...
Model order reduction is an approach for reducing size, complexity, and computation cost of mathemat...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. Th...
Model Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in o...
Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dram...
The proper orthogonal decomposition combined with the discrete empirical interpolation method is inv...
This paper introduces an interpolation method based on snapshot approach to reduce the order of a no...
This PhD thesis aim at developing original, fast and accurate models well adapted to the growing com...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
The aim of this paper is to investigate on various methods of reducing the computational complexity,...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
This chapter contains three advanced topics in model order reduction (MOR): nonlinear MOR, MOR for m...
Electrical circuits usually contain nonlinear components. Hence we are interested in MOR methods tha...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
In this paper, proper orthogonal decomposition (POD) method is employed to build a reduced-order mod...
Model order reduction is an approach for reducing size, complexity, and computation cost of mathemat...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. Th...
Model Order Reduction (MOR) methods are more and more applied on many di erent elds of physics in o...
Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dram...
The proper orthogonal decomposition combined with the discrete empirical interpolation method is inv...
This paper introduces an interpolation method based on snapshot approach to reduce the order of a no...
This PhD thesis aim at developing original, fast and accurate models well adapted to the growing com...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
The aim of this paper is to investigate on various methods of reducing the computational complexity,...
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric so...
This chapter contains three advanced topics in model order reduction (MOR): nonlinear MOR, MOR for m...
Electrical circuits usually contain nonlinear components. Hence we are interested in MOR methods tha...