The aim of the work is to stabilize the unstable index-1 descriptor systems by Riccati-based feedback stabilization via a modified form interpolatory projection-based technique Iterative Rational Krylov Algorithm (IRKA) . The basic IRKAis used to find Reduced Order Models (ROMs) for the stable systems conveniently but it is unsuitable for the unstable systems . In the proposed technique, we implement the initial feedback  within the construction of the projectors of the IRKA approach. The Riccati solution is estimated from the ROM achieved by IRKA and hence the low-rank feedback matrix is attained. The feedback matrix for the full model  is retrieved from the low-rank feedback matrix by the reverse projecting process . Finally, the applicability and efficiency of the proposed method are validated by applying to unstable index-1 descriptor systems. The  simulation is done numerically using MATLABand the achieved results are discussed in both tabular and graphical approaches .
The work aims to stabilize the unstable index-1 descriptor systems by Riccati-based feedback stabilization via a modified form of Iterative Rational Krylov Algorithm (IRKA) , which is a bi-tangential interpolation-based technique. In the basic IRKA, for the stable systems the Reduced Order Models (ROMs) can be found conveniently, but it is unsuitable for the unstable ones . In the proposed technique, the initial feedback is implemented within the construction of the projectors of the IRKA approach. The solution of the Riccati equation is estimated from the ROM achieved by IRKA and hence the low-rank feedback matrix is attained. Using the reverse projecting process, for the full model the optimal feedback matrix is retrieved from the low-rank feedback matrix . Finally, to validate the aptness and competency of the proposed technique it is applied to unstable index-1 descriptor systems. The comparison of the present work with two previous works is narrated. The simulation is done by numerical computation using MATLAB, and both the tabular method and graphical method are used as the supporting tools of comparative analysis .
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numerically using MATLABand the achieved results are discussed in both tabular and graphical approaches
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