Global Control of Reaction Wheel Pendulum Using Artificial Neural Networks and Extended Linearization


Authors

DOI:

https://doi.org/10.22517/23447214.13871

Keywords:

Global control, Soft commutation, Extended linearization, Energetic models, Artificial Neural Networks

Abstract

In this paper describes the design and simulation of a two-stage hybrid controller for the inverted reaction wheel pendulum (RWP) is presented. In the first stage, the general pendulum arm modeling is performed through a nonlinear model to determine the stored energy in the plant, and using a strategy known as swing up energy regulation, the data required for the training of an artificial neural network are obtained. In the second stage, via a soft switching system, neuronal control is exchanged by a controller based on the extended linearization of the state variables, whereby the permanence of the pendulum in the region of operation is guaranteed. The control strategy proposed shows excellent performance against external disturbance phenomena and ensures the overall operation of the physical system.

 

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Author Biographies

Oscar Danilo Montoya Giraldo, Universidad Tecnológica de Pereira

ESTUDIANTE DE DOCTORADO EN INGENIERÍA Y PROFESOR DEL PROGRAMA DE INGENIERÍA ELÉCTRICA DE LA UNIVERSIDAD TECNOLÓGICA DE PEREIRA.

Carlos Alberto Ramírez Vanegas, Universidad Tecnológica de Pereira

ESTUDIANTE DE DOCTORADO EN CIENCIAS DE LA EDUCACIÓN Y PROFESOR DE CIENCIAS BÁSICAS DE LA UNIVERSIDAD TECNOLÓGICA DE PEREIRA.

Luis Fernando Grisales Noreña, INSTITUTO TECNOLOGICO METROPOLITANO DE MEDELLÍN

PROFESOR DE LA FACULTAD DE INGENIERÍA ELECTROMÉCANICA DEL INSTITUTO TECNOLOGICO METROPOLITANO DE MEDELLÍN

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Published

2017-06-30

How to Cite

Montoya Giraldo, O. D., Ramírez Vanegas, C. A., & Grisales Noreña, L. F. (2017). Global Control of Reaction Wheel Pendulum Using Artificial Neural Networks and Extended Linearization. Scientia Et Technica, 22(2), 130. https://doi.org/10.22517/23447214.13871

Issue

Vol. 22 No. 2 (2017)

Section

Eléctrica

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