Abstract Model Order Reduction (MOR) has demonstrated its robustness and wide use in
engineering and science for the simulation of large-scale mathematical systems over the last …

In this study, we propose a new method for obtaining a reduced order model of high order
linear time-invariant single input–single output (SISO) and multiple input–multiple output …

In this paper, a new technique for order reduction of linear time-invariant systems is
presented. This technique is intended for both single-input single-output (SISO) and multi …

A novel computer aided method is presented that yields Linear Time Invariant Reduced
Order System (LTI-ROS). This is accomplished by using the combined benefits of Big Bang …

A mixed method is proposed for finding stable reduced order models of single-input-single-
output large-scale systems using Pade approximation and the clustering technique. The …

In this paper, a new approach is proposed to approximate the high-order linear time
invariant (LTI) system into its low-order model. The proposed approach is a mixed method of …

A new model reduction method for the simplification and design of a controller for the linear
time-invariant systems is proposed. An improved generalized pole clustering algorithm is …

Most of the physical systems can be represented by mathematical models. The
mathematical procedure of system modeling often leads to a comprehensive description of a …

A new method of model order reduction is introduced by combining the merits of big bang
big crunch (BBBC) optimization technique and stability equation (SE) method. A linear …

A new mixed method for reducing the order of the large‐scale linear dynamic multi‐input‐
multi‐output (MIMO) systems has been presented. In this method, the common denominator …