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Intelligent block spectral factors relocation in a quadrotor unmanned aerial vehicle

Intelligent block spectral factors relocation in a quadrotor unmanned aerial vehicle In the present work, we have proposed a new intelligent design procedure, which will achieve the desired latent-structure specifications via the relocation of spectral factors. The method proposed here allows the assignment of the whole set of latent values/vectors obtained from a desired eigenstructure. The quadrotor robot is a quite complex dynamical coupled nonlinear system, then in order to apply the MIMO linear compensation theory and avoiding the complexity of nonlinear control design we have firstly linearised the plant via a state feedback controller and thereafter a regulation and trajectory tracking problems are accurately treated via block pole placement based on the design of MIMO adaptive neuro-fuzzy compensation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Systems, Control and Communications Inderscience Publishers

Intelligent block spectral factors relocation in a quadrotor unmanned aerial vehicle

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1755-9340
eISSN
1755-9359
DOI
10.1504/IJSCC.2017.087144
Publisher site
See Article on Publisher Site

Abstract

In the present work, we have proposed a new intelligent design procedure, which will achieve the desired latent-structure specifications via the relocation of spectral factors. The method proposed here allows the assignment of the whole set of latent values/vectors obtained from a desired eigenstructure. The quadrotor robot is a quite complex dynamical coupled nonlinear system, then in order to apply the MIMO linear compensation theory and avoiding the complexity of nonlinear control design we have firstly linearised the plant via a state feedback controller and thereafter a regulation and trajectory tracking problems are accurately treated via block pole placement based on the design of MIMO adaptive neuro-fuzzy compensation.

Journal

International Journal of Systems, Control and CommunicationsInderscience Publishers

Published: Jan 1, 2017

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