Title:
Neural-Network Augmentation of Existing Linear Controllers
Neural-Network Augmentation of Existing Linear Controllers
| dc.contributor.author | Sharma, Manu | |
| dc.contributor.author | Calise, Anthony J. | |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Aerospace Engineering | |
| dc.contributor.corporatename | Barron Associates, Inc. | |
| dc.date.accessioned | 2010-11-10T21:23:06Z | |
| dc.date.available | 2010-11-10T21:23:06Z | |
| dc.date.issued | 2005-01 | |
| dc.description | Published in Journal of Guidance Control and Dynamics, Vol. 28, No. 1, January-February 2005. | en_US |
| dc.description | Presented as Paper 2001-4163 at the Guidance, Navigation, and Control Conference, Montreal, Canada, 7 August 2001; received 28 July 2003; revision received 8 April 2004; accepted for publication 9 April 2004. Copyright copyright 2004 by Manu Sharma and Anthony J. Calise. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. | |
| dc.description.abstract | A method to augment existing linear controllers with a multilayer neural network is presented. The neural network is adapted online to ensure desired closed-loop response in the face of parametric plant uncertainty; no off-line training is required. The benefit of this scheme is that the neural-network output is simply added to the nominal control signal, thereby preserving the existing control architecture. Furthermore, the nominal control signal is only modified if the desired closed-loop response is not met. This method applies to a large class of modern and classical linear controllers. Stability guarantees are provided via Lyapunov-like analysis, and the efficacy of this scheme is illustrated through two numerical examples. | en_US |
| dc.identifier.issn | 0731-5090 | |
| dc.identifier.uri | http://hdl.handle.net/1853/35905 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | American Institute of Aeronautics and Astronautics, Inc. | |
| dc.subject | Augmentation of existing controllers | en_US |
| dc.subject | Neural network | en_US |
| dc.subject | Adaptive control | en_US |
| dc.title | Neural-Network Augmentation of Existing Linear Controllers | en_US |
| dc.type | Text | |
| dc.type.genre | Article | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | Daniel Guggenheim School of Aerospace Engineering | |
| local.contributor.corporatename | Aerospace Design Group | |
| local.contributor.corporatename | College of Engineering | |
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