Model reduction of non-minimal discrete-time linear-time-invariant systems

D. K. Arif*, D. Adzkiya, E. Apriliani, I. N. Khasanah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Model reduction is a method for reducing the order of mathematical models such that the behavior of reduced system is similar with the original system. Many models in real systems are non minimal. However, to the best of our knowledge, there is no literature that discusses the model reduction of non-minimal systems. Therefore in this paper, we propose a procedure for model reduction of non-minimal discrete-time linear-time-invariant systems by using balanced truncation methods. In this paper, we generate an algorithm to reduce non-minimal discrete-time linear-time-invariant systems. From the simulation results, we obtain a reduced system with similar behavior with the original system. Furthermore, we also conclude that the behavior of the reduced system is very close to the original system in high frequency.

Original languageEnglish
Pages (from-to)377-391
Number of pages15
JournalMalaysian Journal of Mathematical Sciences
Issue number3
Publication statusPublished - 1 Sept 2017


  • Balanced truncation methods
  • Model reduction
  • Non-minimal discrete-time linear-time-invariant systems


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