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| Title: | Decentralized neural network control of a class of large-scale systems with unknown interconnection | |
| Author (s): | Liu, Wenxin Sarangapani, Jagannathan Wunsch, Donald C. Crow, Mariesa L. | |
| Department/Lab Affiliations: | Applied Computational Intelligence Laboratory Computer Science Electrical and Computer Engineering Energy Research and Development Center Engineering Management & Systems Engineering Intelligent Systems Center | |
| Keywords: | adaptive neural network control backstepping decentralized control neural networks | |
| Issue Date: | 2004 | |
| Publisher: | Institute of Electrical and Electronics Engineers IEEE | |
| Citation: | Liu, W., Jagannathan, S., Wunsch, D.C., and Crow, M.L. “Decentralized neural network control of a class of large-scale systems with unknown interconnections.” 43rd IEEE Conference on Decision and Control, 2004, vol. 5, pp. 4972-4977. | |
| Abstract: | A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set. | |
| Type: | Article - Conference proceedings text | |
| In Title: | 43rd IEEE Conference on Decision and Control | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. allows publisher's final version to be uploaded FULL COPYRIGHT INFORMATION: | |
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| title | Decentralized neural network control of a class of large-scale systems with unknown interconnection | |
| contributor.author | Liu, Wenxin | |
| contributor.author | Sarangapani, Jagannathan | |
| contributor.author | Wunsch, Donald C. | |
| contributor.author | Crow, Mariesa L. | |
| contributor.deptlab | Applied Computational Intelligence Laboratory | |
| contributor.deptlab | Computer Science | |
| contributor.deptlab | Electrical and Computer Engineering | |
| contributor.deptlab | Energy Research and Development Center | |
| contributor.deptlab | Engineering Management & Systems Engineering | |
| contributor.deptlab | Intelligent Systems Center | |
| contributor.sponsor | National Science Foundation | |
| subject | adaptive neural network control | |
| subject | backstepping | |
| subject | decentralized control | |
| subject | neural networks | |
| date.issued | 2004 | |
| publisher | Institute of Electrical and Electronics Engineers IEEE | |
| identifier.citation | Liu, W., Jagannathan, S., Wunsch, D.C., and Crow, M.L. “Decentralized neural network control of a class of large-scale systems with unknown interconnections.” 43rd IEEE Conference on Decision and Control, 2004, vol. 5, pp. 4972-4977. | |
| identifier.pub.URI | ||
| description.abstract | A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights | allows publisher's final version to be uploaded | |
| rights.URI | ||
| rights.URI | ||
| rights.URI | ||
| relation.isPartOf | 43rd IEEE Conference on Decision and Control | |
| date.accessioned | 2008-07-25T15:32:08Z | |
| date.available | 2008-08-05T14:29:41Z | |
| identifier.persist.URI | ||
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