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Determination of the Central Pattern Generator Parameters by a Neuro-Fuzzy Evolutionary Algorithm

  • Edgar Mario Rico Mesa
  • Jesús-Antonio Hernández-RiverosEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1066)

Abstract

The selection of appropriate parameters of a Central Pattern Generator (CPG) facilitates its use on applications in robotics. A Central Pattern Generator is class of oscillator represented by a system of n differential equations of first order with m parameters, finding those m parameters to match a specific behavior is a complex problem to solve. For the development of applications in robotics, such as locomotion, the CPG have been applied as a decentralized control system. In this work, a Neuro-Fuzzy Evolutionary procedure is proposed to determine the parameters of a CPG for a specific cases of 2, 3, 4, 5 and 6 neurons. The developed methodology is presented in detail. The proposed algorithm guarantees a given response in the frequency and amplitude into the ranges required.

Keywords

CPG Digital filter Fuzzy classifier Recurrent Neural Network Genetic algorithms 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.SENAMedellínColombia
  2. 2.Universidad Nacional de ColombiaMedellínColombia

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