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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Lastly, some numerical examples are given in order to explain how this method works.
📌 3 Key Takeaways
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Objective & Hypothesis:The aim of this paper is to examine a numerical method for the computation of approximate solution of the continuous-time algebraic Riccati equation using Krylov subspace matrix.
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Key Findings & Data:First of all, Global Arnoldi process is initiated to construct an orthonormal basis.
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Conclusion & Impact:Lastly, some numerical examples are given in order to explain how this method works.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Algebraic Riccati equation · Krylov subspace · Arnoldi.
Abstract
The aim of this paper is to examine a numerical method for the computation of approximate solution of the continuous-time algebraic Riccati equation using Krylov subspace matrix. First of all, Global Arnoldi process is initiated to construct an orthonormal basis. In addition, Krylov subspace matrix is employed as projection method because it is one of the frequently referred method in the literature. Lastly, some numerical examples are given in order to explain how this method works.
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Cite This Article
SERİM, A. B. Ö., BAYRAM, M. (2013). Low rank approximate solutions obtained from a different application of global arnoldi method. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 31 - Sayı: 1, 34–42. https://ajindex.com/articles/419231