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| Title: | Neuroadaptive model following controller design for a nonaffine UAV model | |
| Author (s): | Unnikrishnan, Nishant Balakrishnan, S. N. | |
| Department/Lab Affiliations: | Mechanical & Aerospace Engineering | |
| Keywords: | adaptive control adaptive control design aerospace control control system synthesis degree of freedom model neuroadaptive model neurocontrollers nonaffine UAV Model nonlinear control systems nonlinear system online neural network parameter uncertainty remotely operated vehicles unmanned aerial vehicle unmodeled dynamics | |
| Issue Date: | 2006 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Unnikrishnan, N.; Balakrishnan, S. N. "Neuroadaptive model following controller design for a nonaffine UAV model" American Control Conference, 2006, 14-16 June 2006 Pages: 6 pp. | |
| Abstract: | This paper proposes a new model-following adaptive control design technique for nonlinear systems that are nonaffine in control. The adaptive controller uses online neural networks that guarantee tracking in the presence of unmodeled dynamics and/or parameter uncertainties present in the system model through an online control adaptation procedure. The controller design is carried out in two steps: (i) synthesis of a set of neural networks which capture the unmodeled (neglected) dynamics or model uncertainties due to parametric variations and (ii) synthesis of a controller that drives the state of the actual plant to that of a reference model. This method is tested using a three degree of freedom model of a UAV. Numerical results which demonstrate these features and clearly bring out the potential of the proposed approach are presented in this paper. | |
| 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 | Neuroadaptive model following controller design for a nonaffine UAV model | |
| contributor.author | Unnikrishnan, Nishant | |
| contributor.author | Balakrishnan, S. N. | |
| contributor.deptlab | Mechanical & Aerospace Engineering | |
| subject | adaptive control | |
| subject | adaptive control design | |
| subject | aerospace control | |
| subject | control system synthesis | |
| subject | degree of freedom model | |
| subject | neuroadaptive model | |
| subject | neurocontrollers | |
| subject | nonaffine UAV Model | |
| subject | nonlinear control systems | |
| subject | nonlinear system | |
| subject | online neural network | |
| subject | parameter uncertainty | |
| subject | remotely operated vehicles | |
| subject | unmanned aerial vehicle | |
| subject | unmodeled dynamics | |
| date.issued | 2006 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Unnikrishnan, N.; Balakrishnan, S. N. "Neuroadaptive model following controller design for a nonaffine UAV model" American Control Conference, 2006, 14-16 June 2006 Pages: 6 pp. | |
| identifier.pub.URI | ||
| description.abstract | This paper proposes a new model-following adaptive control design technique for nonlinear systems that are nonaffine in control. The adaptive controller uses online neural networks that guarantee tracking in the presence of unmodeled dynamics and/or parameter uncertainties present in the system model through an online control adaptation procedure. The controller design is carried out in two steps: (i) synthesis of a set of neural networks which capture the unmodeled (neglected) dynamics or model uncertainties due to parametric variations and (ii) synthesis of a controller that drives the state of the actual plant to that of a reference model. This method is tested using a three degree of freedom model of a UAV. Numerical results which demonstrate these features and clearly bring out the potential of the proposed approach are presented in this paper. | |
| 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 | 2007-04-05T14:27:13Z | |
| date.available | 2007-04-05T14:27:13Z | |
| identifier.persist.URI | ||
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