Sharif University of Technology Scientia Iranica 1026-3098 25 3 2018 06 01 Lyapunov-Global-Lanczos Algorithm for Model Order Reduction & Adaptive PI Controller of Large Scale Electrical Systems 1616 1628 4368 10.24200/sci.2017.4368 EN Kouki Mohamed Universit´e de Tunis El Manar, Institut Sup´erieur d’Informatique et de Gestion de Kairouan, LR-11-ES20 Laboratoire Analyse, Conception et Commande des Systemes, BP 37, LE BELVEDERE 1002, Tunis, Tunisie Abbes Mehdi Universit´e de Tunis El Manar, Institut Sup´erieur d’Informatique et de Gestion de Kairouan, LR-11-ES20 Laboratoire Analyse, Conception et Commande des Systemes, BP 37, LE BELVEDERE 1002, Tunis, Tunisie Mami Abdelkader Universit´e de Tunis El Manar, Institut Sup´erieur d’Informatique et de Gestion de Kairouan, LR-11-ES20 Laboratoire Analyse, Conception et Commande des Systemes, BP 37, LE BELVEDERE 1002, Tunis, Tunisie Journal Article 2016 02 15 Mathematical modeling of complex electrical systems, has led us to linear mathematical models of higher order. Consequently, it is difficult to analyse and to design a control strategy of these systems. The order reduction is an important and effective tool to facilitate the handling and designing of a control strategy. In this paper we present, firstly, a reduction method which is based on the Krylov subspace and Lyapunov  techniques, that we call Lyapunov-Global-Lanczos. This method minimizes the H1 norm error, absolute error and preserves the stability of the reduced system. It also provides a better reduced system of order 1, with closer behaviour to the original system. This first order system is used to design PI (Proportional-Integral) controller. Secondly, we implement an adaptive digital PI controller in a microcontroller. It calculates the PI parameters in real time, referring to the error between the desired and measured outputs and the initial values of PI controller, that were determined from the first order system. Two simulation examples and a real time experimentation are presented to show the effectiveness of the proposed algorithms. https://scientiairanica.sharif.edu/article_4368_ae0909a324fb2530e205e52d40266418.pdf