Abstract
This paper presents the stability analysis, synthesis, and performance optimization of a radial-basis-function neural-network based control system. Global stability conditions will be derived in terms of matrix measure. Based on the derived stability conditions, connection weights of the radial-basis-function neural-network based controller can be optimized by genetic algorithm (GA) subject to the system stability. Furthermore, the system performance will also be optimized by the GA. An application example on stabilizing an inverted pendulum will be given to illustrate the design procedure and merits of the proposed approach.
Original language | English |
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Title of host publication | IECON Proceedings (Industrial Electronics Conference) |
Pages | 2813-2818 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 1 Dec 2004 |
Event | IECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society - Busan, Korea, Republic of Duration: 2 Nov 2004 → 6 Nov 2004 |
Conference
Conference | IECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society |
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Country/Territory | Korea, Republic of |
City | Busan |
Period | 2/11/04 → 6/11/04 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering