Stability Preserving Model Reduction Frameworks for Control of Complex Dynamical Systems / (Record no. 616123)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02462nam a22001817a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260207145030.0 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.382,LAT |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Latif, Muhammad |
| 9 (RLIN) | 32948 |
| 245 ## - TITLE STATEMENT | |
| Title | Stability Preserving Model Reduction Frameworks for Control of Complex Dynamical Systems / |
| Statement of responsibility, etc. | Muhammad Latif |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Rawalpindi, |
| Name of publisher, distributor, etc. | MCS (NUST), |
| Date of publication, distribution, etc. | 2025 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxi, 209 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | In the domain of control systems engineering, mathematical modeling constitutes the<br/>cornerstone for the analysis of dynamical systems, particularly when systems become<br/>increasingly complex. However, the computational demands of simulating large-scale<br/>systems, incorporating various types of equations, present formidable challenges. Model<br/>reduction techniques aim to approximate complex, high-order systems with simpler,<br/>lower-order models while retaining acceptable accuracy. These techniques ultimately<br/>simplify the design, modeling, and simulation of large-scale systems.<br/>This dissertation delves into model reduction techniques tailored for large-scale highdimensional<br/>systems, leveraging balanced structures for improving efficiency.<br/>Initially, this research carries out literature review of existing model order reduction<br/>techniques in order to examine their limitations. Over the past few decades, numerous<br/>model order reduction methods have been proposed in the literature. Among these, the<br/>balanced truncation method is widely adopted due to its simplicity, ability to preserve<br/>stability in reduced models, and incorporation of a priori error bounds. The method<br/>involves balancing the original system and subsequently truncating the least controllable<br/>and observable states to derive reduced order models. However, in literature we find<br/>disadvantages of balanced truncation approach, because in few of the cases, it fails<br/>to guarantee the positive definiteness of associated Gramians, leading to potential<br/>instability in reduced models. To address this limitation, several alternate methods have<br/>also been proposed in the literature. However, these methods often impose restrictive conditions and may introduce significant approximation errors. Few of these, prove<br/>realization-dependent; while others increase computationally complexity, hindering their<br/>practical usage. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | PhD Electrical Engineering Thesis |
| 9 (RLIN) | 133107 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Geographic name | PhD EE Thesis |
| 9 (RLIN) | 133108 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervised by Dr. Muhammad Imran |
| 9 (RLIN) | 132697 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 02/07/2026 | 621.382,LAT | MCSPhD EE-30 | 02/07/2026 | 02/07/2026 | Thesis |