Model Reduction by New Clustering Method and Frequency Response Matching

2016 ◽  
Vol 28 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Sharad Kumar Tiwari ◽  
Gagandeep Kaur
Keyword(s):  
Frequency Response ◽  
Model Reduction ◽  
Clustering Method ◽  
Frequency Response Matching

A Method of Model Reduction

1986 ◽  
Vol 108 (4) ◽  
pp. 368-371 ◽  
Author(s):  
Jium-Ming Lin ◽  
Kuang-Wei Han
Keyword(s):  
Transfer Function ◽  
Frequency Response ◽  
Model Reduction ◽  
Control Systems ◽  
Response Curve ◽  
Nonlinear Control Systems ◽  
Frequency Response Curve ◽  
Stability Boundaries ◽  
Parameter Variations ◽  
The Stability

In this brief note, the effects of model reduction on the stability boundaries of control systems with parameter variations, and the limit-cycle characteristics of nonlinear control systems are investigated. In order to reduce these effects, a method of model reduction is used which can approximate the original transfer function at S=0, S=∞, and also match some selected points on the frequency response curve of the original transfer function. Examples are given, and comparisons with the methods given in current literature are made.

Discretization of Existing Continuous Control Systems

1997 ◽  
Vol 119 (2) ◽  
pp. 315-318 ◽  
Author(s):  
Somnath Pan ◽  
Jayanta Pal
Keyword(s):  
Frequency Response ◽  
Control Systems ◽  
Closed Loop ◽  
Digital System ◽  
New Method ◽  
Continuous Control ◽  
Algebraic Equations ◽  
Analog System ◽  
Linear Algebraic Equations ◽  
Frequency Response Matching

A new method is presented for discretizing an existing analog controller. The method is based on frequency response matching of the closed-loop digital system with that of the original analog system. The method requires solution of linear algebraic equations and is computationally simple. Efficacy of the method is illustrated through examples taken from the literature.

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