A new approach to order reduction using stability equation and big bang big crunch optimization

By S. R. Desai, Rajendra Prasad. 2013

95 citations recorded by the source corpus.

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-continuous single-input single-output system of higher order is considered and reduced to a lower order system. The denominator polynomial of the reduced system is obtained by SE method, whereas the numerator terms are generated using BBBC optimization. Furthermore, step and frequency responses of the original reduced system are plotted. The superiority of the proposed method is justified by solving numerical examples from the available literature and comparing the reduced systems in terms of error indices.

Subfields: Control and Systems Engineering, Statistical and Nonlinear Physics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1b60392954135d43ce9946102156b549e81113f7

How researchers see this paper

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In Control and Systems Engineering

1. Zidong Wang
2. Huijun Gao
3. Hongli Dong
4. Jun Hu
5. Qing-Long Han
6. James Lam
7. Tongwen Chen
8. Peng Shi

In Statistical and Nonlinear Physics

1. Huijun Gao
2. Zidong Wang
3. Hamid Reza Karimi

Citations in the corpus

• Recent Advances on Recursive Filtering and Sliding Mode Design for Networked Nonlinear Stochastic Systems: A Survey (2013, background): “[86] S.”