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Neural Processing Letters

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01-08-2018

Real-Time Implementation of a Neural Integrator Backstepping Control via Recurrent Wavelet First Order Neural Network

Authors: Luis A. Vázquez, Francisco Jurado, Carlos E. Castañeda, Alma Y. Alanis

Published in: Neural Processing Letters | Issue 3/2019

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Abstract

Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat, and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using continuous wavelet transform. Continuous wavelets are favoured when a high temporal resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called recurrent wavelet first-order neural network, is proposed in order to achieve a better identification of the behavior of dynamic systems. The effectiveness of our proposal is explored through the design of a centralized neural integrator backstepping control scheme for a two degree-of-freedom robot manipulator evolving in the vertical plane. The performance of the overall neural identification and control scheme is verified through numerical simulation using the mathematical model for a benchmark prototype. Moreover, real-time results validate the effectiveness of our proposal when using a robotic arm, of our own design, powered by industrial servomotors.

previous article Multi-Delay-Dependent Exponential Synchronization for Neutral-Type Stochastic Complex Networks with Markovian Jump Parameters via Adaptive Control

next article Event Triggered Finite Time Boundedness of Uncertain Markov Jump Neural Networks with Distributed Time Varying Delays

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Title: Real-Time Implementation of a Neural Integrator Backstepping Control via Recurrent Wavelet First Order Neural Network
Authors: Luis A. Vázquez
Francisco Jurado
Carlos E. Castañeda
Alma Y. Alanis
Publication date: 01-08-2018
Publisher: Springer US
Published in: Neural Processing Letters / Issue 3/2019
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-018-9893-6

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