Sparsity-Preserving Two-Sided Iterative Algorithm for Riccati-Based Boundary Feedback Stabilization of the Incompressible Navier-Stokes Flow

被引:1
作者
Islam, Md. Toriqul [1 ]
Uddin, Mahtab [1 ,2 ]
Uddin, M. Monir [3 ]
Khan, Md. Abdul Hakim [1 ]
Hossain, Md. Tanzim [4 ]
机构
[1] Bangladesh Univ Engn Technol, Dept Math, Dhaka 1000, Bangladesh
[2] United Int Univ, Inst Nat Sci, Dhaka 1212, Bangladesh
[3] North South Univ, Dept Math & Phys, Dhaka 1229, Bangladesh
[4] North South Univ, Dept Elect & Comp Engn, Dhaka 1229, Bangladesh
关键词
LARGE-SCALE; MODEL-REDUCTION; DESCRIPTOR SYSTEMS; BALANCED TRUNCATION; EQUATIONS;
D O I
10.1155/2022/4435167
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, we explore the Riccati-based boundary feedback stabilization of the incompressible Navier-Stokes flow via the Krylov subspace techniques. Since the volume of data derived from the original models is gigantic, the feedback stabilization process through the Riccati equation is always infeasible. We apply a Script capital H-2 optimal model-order reduction scheme for reduced-order modeling, preserving the sparsity of the system. An extended form of the Krylov subspace-based two-sided iterative algorithm (TSIA) is implemented, where the computation of an equivalent Sylvester equation is included for minimizing the computation time and enhancing the stability of the reduced-order models with satisfying the Wilson conditions. Inverse projection approaches are applied to get the optimal feedback matrix from the reduced-order models. To validate the efficiency of the proposed techniques, transient behaviors of the target systems are observed incorporating the tabular and figurative comparisons with MATLAB simulations. Finally, to reveal the advancement of the proposed techniques, we compare our work with some existing works.
引用
收藏
页数:14
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