dc.contributor.author | Polycarpou, Marios M. | en |
dc.contributor.author | Ioannou, Petros A. | en |
dc.creator | Polycarpou, Marios M. | en |
dc.creator | Ioannou, Petros A. | en |
dc.date.accessioned | 2019-12-02T10:37:59Z | |
dc.date.available | 2019-12-02T10:37:59Z | |
dc.date.issued | 1995 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/57550 | |
dc.description.abstract | This paper considers the design of stable adaptive neural controllers for uncertain nonlinear dynamical systems with unknown nonlinearities. The Lyapunov synthesis approach is used to develop state-feedback adaptive control schemes based on a general class of nonlinearly parametrized neural network models. The key assumptions are that the system uncertainty satisfies a 'strict-feedback' condition and that the network reconstruction error and higher-order terms (with respect to the parameter estimates) satisfy certain bounding conditions. An adaptive bounding design is used to show that the overall neural control system guarantees semi-global uniform ultimate boundedness within a neighborhood of zero tracking error. | en |
dc.publisher | IEEE | en |
dc.source | Proceedings of the IEEE Conference on Decision and Control | en |
dc.source | Proceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-0029483480&partnerID=40&md5=979a8f085451529e59651f97ee2424bb | |
dc.subject | Mathematical models | en |
dc.subject | Neural networks | en |
dc.subject | Approximation theory | en |
dc.subject | Control theory | en |
dc.subject | Feedback control | en |
dc.subject | Nonlinear control systems | en |
dc.subject | Lyapunov methods | en |
dc.subject | Control system synthesis | en |
dc.subject | Control nonlinearities | en |
dc.subject | System stability | en |
dc.subject | Intelligent control | en |
dc.subject | Adaptive control systems | en |
dc.subject | Adaptive bounding techniques | en |
dc.subject | Nonlinear dynamic systems | en |
dc.subject | Stable neural control systems | en |
dc.title | Adaptive bounding techniques for stable neural control systems | en |
dc.type | info:eu-repo/semantics/conferenceObject | |
dc.description.volume | 3 | |
dc.description.startingpage | 2442 | |
dc.description.endingpage | 2447 | |
dc.author.faculty | Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics | |
dc.type.uhtype | Conference Object | en |
dc.description.notes | <p>Sponsors: IEEE | en |
dc.description.notes | Conference code: 44367 | en |
dc.description.notes | Cited By :7</p> | en |
dc.contributor.orcid | Ioannou, Petros A. [0000-0001-6981-0704] | |
dc.contributor.orcid | Polycarpou, Marios M. [0000-0001-6495-9171] | |
dc.gnosis.orcid | 0000-0001-6981-0704 | |
dc.gnosis.orcid | 0000-0001-6495-9171 | |