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| Title: | Non-linear system control using path generating neural networks |
| Author (s): | Woodley, R. S. Acar, Levent |
| Department/Lab Affiliations: | Electrical and Computer Engineering |
| Keywords: | control non-linear augmentation non-linear systems |
| Issue Date: | 1998 |
| Publisher: | American Society of Mechanical Engineers ASME |
| Citation: | Woodley, R. S. and Levent Acar. "Non-linear system control using path generating neural networks." Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE 1998), Volume 8, 1998: 599-604 |
| Abstract: | An increasing amount of literature is available on the control of non-linear systems. For many of these systems, linear design techniques are ineffective. However, a non-linear augmentation of the linear control is sometimes able to perform the control. Determining the augmenting signal is a formidable task. However, recent work in the area of path planning has given rise to some useful tools. These tools can be used to design a complete controller. The final design takes advantage of the mapping abilities of neural networks to perform path planning. A path planning algorithm, taken from previously published work, was used to generate training data for the neural network. The results of simulation tests show that the controller composed of a linear gain and a path planning neural network was capable of controlling the non-linear system. The results are for a small class of non-trivial trajectories. Further work is planned to generalize the results. |
| Type: | Article - Conference proceedings text |
| In Title: | ANNIE 1998 |
| 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. Pre-print: author cannot archive; Post-print: author cannot archive; FULL COPYRIGHT INFORMATION: |
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| title | Non-linear system control using path generating neural networks |
| contributor.author | Woodley, R. S. |
| contributor.author | Acar, Levent |
| contributor.deptlab | Electrical and Computer Engineering |
| contributor.sponsor | National Science Foundation |
| subject | control |
| subject | non-linear augmentation |
| subject | non-linear systems |
| date.issued | 1998 |
| publisher | American Society of Mechanical Engineers ASME |
| identifier.citation | Woodley, R. S. and Levent Acar. "Non-linear system control using path generating neural networks." Intelligent Engineering Systems Through Artificial Neural Networks (ANNIE 1998), Volume 8, 1998: 599-604 |
| identifier.pub.URI | |
| description.abstract | An increasing amount of literature is available on the control of non-linear systems. For many of these systems, linear design techniques are ineffective. However, a non-linear augmentation of the linear control is sometimes able to perform the control. Determining the augmenting signal is a formidable task. However, recent work in the area of path planning has given rise to some useful tools. These tools can be used to design a complete controller. The final design takes advantage of the mapping abilities of neural networks to perform path planning. A path planning algorithm, taken from previously published work, was used to generate training data for the neural network. The results of simulation tests show that the controller composed of a linear gain and a path planning neural network was capable of controlling the non-linear system. The results are for a small class of non-trivial trajectories. Further work is planned to generalize the results. |
| type | Article - Conference proceedings |
| type.DCMIType | text |
| relation.isPartOf | ANNIE 1998 |
| 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 | Pre-print: author cannot archive; Post-print: author cannot archive; |
| rights.URI | |
| rights.URI | |
| identifier.persist.URI | |
| date.available | 2009-04-14T21:04:57Z |