Enhancements in Performance of Reduced Order Modelling of Large-Scale Control Systems

2020 ◽  
pp. 69-78
Author(s):  
Ankur Gupta ◽  
Amit Kumar Manocha
Keyword(s):  
Control Systems ◽  
Large Scale ◽  
Reduced Order ◽  
Reduced Order Modelling ◽  
Scale Control

scholarly journals Model reduction methods based on Krylov subspaces

Acta Numerica ◽  
2003 ◽  
Vol 12 ◽  
pp. 267-319 ◽  
Author(s):  
Roland W. Freund
Keyword(s):  
Large Scale ◽  
Krylov Subspace ◽  
Circuit Simulation ◽  
Krylov Subspaces ◽  
Lanczos Algorithm ◽  
Linear Dynamical Systems ◽  
Reduced Order ◽  
Reduced Order Modelling ◽  
Reduction Methods ◽  
Modelling Techniques

In recent years, reduced-order modelling techniques based on Krylov-subspace iterations, especially the Lanczos algorithm and the Arnoldi process, have become popular tools for tackling the large-scale time-invariant linear dynamical systems that arise in the simulation of electronic circuits. This paper reviews the main ideas of reduced-order modelling techniques based on Krylov subspaces and describes some applications of reduced-order modelling in circuit simulation.

Training for the Planning of Large-Scale Control Systems

1983 ◽  
Vol 16 (6) ◽  
pp. 77-79
Author(s):  
A. Caballero ◽  
Aleksander Shashkin
Keyword(s):  
Control Systems ◽  
Large Scale ◽  
Scale Control

MANAGING COMPLEXITY IN LARGE SCALE CONTROL SYSTEMS

2006 ◽  
Vol 39 (14) ◽  
pp. 82-87
Author(s):  
K. Halmevaara ◽  
H. Hyötyniemi
Keyword(s):  
Control Systems ◽  
Large Scale ◽  
Managing Complexity ◽  
Scale Control

Simulation for training and decision-making in large-scale control systems

SIMULATION ◽  
1980 ◽  
Vol 35 (2) ◽  
pp. 45-48 ◽  
Author(s):  
Laurence E. Fogarty
Keyword(s):  
Decision Making ◽  
Control Systems ◽  
Large Scale ◽  
Scale Control
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