Abstract
In this paper, a neurodynamic optimization approach is proposed for robust pole assignment of fractional-order control systems. Compared with integral-order systems, the pole assignment of fractional-order systems is more challenging due to variability of stability region. The robust pole assignment is formulated as a constrained optimization problem, and a robustness measure is derived as a pseudoconvex objective function to be minimized. A recurrent neural network is employed for computing optimal solutions in real time. Simulation results are given to substantiate the efficacy and superiority of the proposed neurodynamic optimization approach.
| Original language | English |
|---|---|
| Title of host publication | 2017 13th IEEE International Conference on Control & Automation (ICCA) |
| Publisher | IEEE Computer Society |
| Pages | 143-148 |
| ISBN (Print) | 9781538626795 |
| DOIs | |
| Publication status | Published - 3 Jul 2017 |
| Event | 13th IEEE International Conference on Control and Automation (IEEE ICCA 2017) - Metropol Lake Resort, Ohrid, Macedonia, The Former Yugoslav Republic of Duration: 3 Jul 2017 → 6 Jul 2017 https://controls.papercept.net/conferences/scripts/rtf/ICCA17_ContentListWeb_1.html http://uav.ece.nus.edu.sg/~icca17/venue.html |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 1948-3449 |
| ISSN (Electronic) | 1948-3457 |
Conference
| Conference | 13th IEEE International Conference on Control and Automation (IEEE ICCA 2017) |
|---|---|
| Place | Macedonia, The Former Yugoslav Republic of |
| City | Ohrid |
| Period | 3/07/17 → 6/07/17 |
| Internet address |
Research Keywords
- Intelligent and AI Based Control
- Fuzzy and Neural Systems
- Robust Control and Systems
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