Award Date

1-1-1994

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Electrical and Computer Engineering

Number of Pages

77

Abstract

The theory of Gaussian radial based function neural networks is developed along with a stable adaptive weight training law founded upon Lyapunov stability theory. This is applied to the control of a nonlinear multi-linked robotic manipulator for the general case of N links. Simulations of a two link system are performed and demonstrate the derived principles.

Keywords

Application; Function; Gaussian; Manipulator; Networks; Neural; Radial; Robotic

Controlled Subject

Electrical engineering; Artificial intelligence

File Format

pdf

File Size

2181.12 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/2uej-t36q


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