Lecturer

Asib Mostakim Fony

Educational Qualifications:

Job Experience: 

Academic Publications (Selected):

1. Hasan, S., Fony, A.M. and Uddin, M.M., 2019, February. Reduced model based feedback stabilization of large-scale sparse power system model. In 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE.
   Abstract: 
   Linearizing a power system model around the equilibrium point we may obtain unstable large-scale sparse differential-algebraic equations (DAEs) with index 1 form. Riccati-based feedback stabilization of such large-scale unstable system is a challenging task. This paper shows that the Riccati-based feedback stabilization matrix for the original unstable system can be computed efficiently from the reduced order state space system. For this purpose we apply the balanced truncation (BT) to the large-scale unstable index 1 DAEs for reduced-order state space model. To implement the BT, we efficiently solve two Lyapunov equations with respect to the Bernoulli stabilized system. The efficiency of the proposed technique is tested by applying to a data set of Brazilian power system model.
    
2. Du, X., Iqbal, K.I.B., Uddin, M.M., Fony, A.M., Hossain, M.T., Ahmad, M.I. and Hossain, M.S., 2021. Computational techniques for H2 optimal frequency-limited model order reduction of large-scale sparse linear systems. Journal of Computational Science, 55, p.101473.
   Abstract:
   We consider the problem of frequency limited H2">�2 optimal model order reduction for large-scale sparse linear systems. A set of first-order H2">�2 optimality conditions are derived for the frequency limited model order reduction problem. These conditions involve the solution of two frequency limited Sylvester equations that are known to be computationally complex. We discuss a framework for solving these matrix equations efficiently. The idea is also extended to the frequency limited H2">�2 optimal model order reduction of index-1 descriptor systems. Numerical experiments are carried out using Python programming language and the results are presented to demonstrate the approximation accuracy and computational efficiency of the proposed technique.
   
   
3. Du, X., Uddiny, M.M., Fonyz, A.M., Hossainx, M.T. and Shuzan, M.N.I., 2021. Iterative Rational Krylov Algorithms for model reduction of a class of constrained structural dynamic system with Engineering applications. arXiv preprint arXiv:2101.03053.
   Abstract:
   This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody dynamics, mechatronics and many other branches of sciences and technologies. By deecting the algebraic equations the second-order index-3 system can be altered into an equivalent standard second-order system. This can be done by projecting the system onto the null space of the constraint matrix. However, creating the projector is computationally expensive and it yields huge bottleneck during the implementation. This paper shows how to find a reduce order model without projecting the system onto the null space of the constraint matrix explicitly. To show the efficiency of the theoretical works we apply them to several data of second-order index-3 models and experimental resultants are discussed in the paper.
   
   

Training:

1. Training on Enterprise System Analysis and Design using C-Sharp conducted lsdb-BISEW scholarship program for 1 year.