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Abstract
A new substructure preservation Sylvester-based model order reduction technique with application to power systems is presented in this article. The new approach is intended for multiple-input–multiple-output linear time invariant systems, given in the form of state-space realization with the objective of obtaining a proper reduced-order model (complexity reduction), preserving the dominant eigenvalues of the full-order model as a subset in the reduced model, and maintaining a minimum steady-state error. The proposed reduction method is performed based on transforming the system state matrix into a special form, taking into account the dominant eigenvalues, while the rest of the model transformation is derived utilizing the Sylvester equation formula. Once the system is transformed, the reduced-order model is obtained by truncating the less dominant eigenvalues using the singular perturbation technique. To evaluate the potential of the new approach, results of the proposed technique are compared to some of the well-known methods for model order reduction and relatively recently published work. Results comparison shows the superiority of the new method especially in terms of time convergence.
Acknowledgment
The authors would like to sincerely thank the editor for continuously following the progress of the modification and enhancement of the proposed article. They also thank anonymous reviewers for their valuable comments that have left a positive distinguished difference in the presentation of this article.
Additional information
Notes on contributors
Othman M. K. Alsmadi
Othman M. K. Alsmadi graduated from Tennessee State University in 1993 with a B.S. in electrical engineering (dean's list honors). In 1995, he received his M.S. from the same university supported by a research assistantship funded by NASA. In 1999, he received his Ph.D. with emphasis in control systems from Wichita State University. From 2000–2002, he worked as a senior research engineer at the Caterpillar Inc. (Kansas), performing different research projects task. In 2003, he joined the Department of Electrical Engineering, The University of Jordan, as an assistant professor. Presently, he is an associate professor and has been the chairman of the Electrical Engineering Department since 2011. His current research includes optimal control, model order reduction, system identification, neural networks, and other artificial intelligence techniques.
Saleh S. Saraireh
Saleh S. Saraireh graduated from Mutah University in 2003 with a B.S. in electrical engineering. In 2006, he received his M.S. from the same university. In 2009, he received his Ph.D. in communication engineering. Presently, he is an assistant professor at the Communication and Electronic Engineering Department at Philadelphia University. His research interests are focused on digital signal processing, cryptography, and wireless communication.
Zaer S. Abo-Hammour
Zaer S. Abo-Hammour graduated from Mutah University in 1991 with a B.S. in electrical engineering. In 1998 and 2003, he received his M.S. and Ph.D., respectively, from Pakistan Institute of Engineering and Applied Sciences, majoring in systems engineering. Presently, he is an associate professor at the Mechatronics Engineering Department, The University of Jordan. His research interests are focused on genetic algorithms, control systems, robotics, and numerical fields. He is also a specialist in solar energy systems and fuel efficiency improvements.
Ali H. Al-Marzouq
Ali H. Al-Marzouq received his B.S. in 2011 from the Electrical Engineering Department, The University of Jordan. Presently, he is working for the Amman East Power Plant, Amman, Jordan and working toward the M.S. in renewable energy at University of Jordan. His main interest is focused on control systems.