Clustering Method for Reducing Order of Linear System using Pade Approximation

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A New Technique For Reduced-Order Modelling of Linear Time-Invariant System (2017, methodology): “Furthermore, composite methods are also proposed by various authors in which denominator polynomials are obtained by one method and numerator polynomials are achieved by another method [7,8].”
Model Reduction Using the Balanced Truncation Method and the Padé Approximation Method (2020, methodology): “In [23], cluster centres of the poles of the original plant are determined and the cluster centres are applied to determine the denominator of the lower order system.”
Optimization of LTI Systems Using Modified Clustering Algorithm (2017, methodology): “The step response of reduced system is compared with original system and Vishwakarma [18] as shown in Figure 2(b).”
Order reduction of linear systems with an improved pole clustering (2012, methodology): “The way in which clustering centers are obtained in this paper is similar to the method proposed by Vishwakarma and Prasad (2009) except that the pole cluster obtained in step 3 concentrates on the dominant pole in that particular cluster center.”
Model Order Reduction by Using the Balanced Truncation and Factor Division Methods (2018, methodology): “In [12], pole cluster centers of poles of the original system are determined and these pole cluster centers are used to find the denominator of the reduced model and the numerator is determined by using the Padé approximation method.”