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| Title: | Dynamic re-optimization of a MEMS controller in presence of unmodeled uncertainties | |
| Author (s): | Unnikrishnan, Nishant Durbha, V. Balakrishnan, S. N. | |
| Issue Date: | 2005 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Unnikrishnan, N.; Durbha, V.; Balakrishnan, S. N. "Dynamic Re-optimization of a MEMS Controller in Presence of Unmodeled Uncertainties" CDC-ECC '05. 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference. 12-15 Dec. 2005 Pages: 7540- 7545 | |
| Abstract: | Online trained neural networks have become popular in recent years in designing robust and adaptive controllers for dynamic systems with uncertainties in their system equations because of their universal function approximation property. This paper discusses a technique that dynamically reoptimizes a Single Network Adaptive Critic (SNAC) based optimal controller in the presence of unmodeled uncertainties. The controller design is carried out in two steps: (i) synthesis of a set of online neural networks that capture the uncertainties in the plant equations on-line (ii) re-optimization of the existing optimal controller to drive the states of the plant to a desired reference by minimizing a predefined cost function. The neural network weight update rule for the online networks has been derived using Lyapunov theory that guarantees stability of the error dynamics as well as boundedness of the weights. This approach has been applied in the online reoptimization of a micro-electromechanical device controller and numerical results from simulation studies are presented here. | |
| Type: | Article - Conference proceedings text | |
| 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. FULL COPYRIGHT INFORMATION: | |
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| title | Dynamic re-optimization of a MEMS controller in presence of unmodeled uncertainties | |
| contributor.author | Unnikrishnan, Nishant | |
| contributor.author | Durbha, V. | |
| contributor.author | Balakrishnan, S. N. | |
| date.issued | 2005 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Unnikrishnan, N.; Durbha, V.; Balakrishnan, S. N. "Dynamic Re-optimization of a MEMS Controller in Presence of Unmodeled Uncertainties" CDC-ECC '05. 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference. 12-15 Dec. 2005 Pages: 7540- 7545 | |
| identifier.pub.URI | ||
| description.abstract | Online trained neural networks have become popular in recent years in designing robust and adaptive controllers for dynamic systems with uncertainties in their system equations because of their universal function approximation property. This paper discusses a technique that dynamically reoptimizes a Single Network Adaptive Critic (SNAC) based optimal controller in the presence of unmodeled uncertainties. The controller design is carried out in two steps: (i) synthesis of a set of online neural networks that capture the uncertainties in the plant equations on-line (ii) re-optimization of the existing optimal controller to drive the states of the plant to a desired reference by minimizing a predefined cost function. The neural network weight update rule for the online networks has been derived using Lyapunov theory that guarantees stability of the error dynamics as well as boundedness of the weights. This approach has been applied in the online reoptimization of a micro-electromechanical device controller and numerical results from simulation studies are presented here. | |
| 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.URI | ||
| date.accessioned | 2007-04-05T14:26:06Z | |
| date.available | 2007-04-05T14:26:06Z | |
| identifier.persist.URI | ||
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