A neural network model for goat gait

Liqin Liu; Chunrui Zhang; Liqin Liu; Chunrui Zhang

doi:10.3934/mbe.2024302

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 8: 6898-6914. doi: 10.3934/mbe.2024302

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Research article

A neural network model for goat gait

Liqin Liu ,
Chunrui Zhang ^,

Department of Mathematics, Northeast Forestry University, Harbin 150040, China

Received: 15 May 2024 Revised: 26 July 2024 Accepted: 14 August 2024 Published: 21 August 2024

In this paper, our main objective was to investigate the central pattern generator (CPG) neural network model for quadruped gait with time delay. First, we computed the normal form of the model on the center manifold, the bifurcation direction, and stability conditions of the bifurcating periodic solutions. Second, we applied the CPG model for quadruped gait to obtain reference models for goat's diagonal trotting gait on the flat ground and walking gait on the 18 degree slope through the trust region inversion algorithm. Finally, we performed numerical simulations to support theoretical analysis.
- time delay neural network,
- quadruped gait CPG model,
- Hopf bifurcation,
- goat gait
Citation: Liqin Liu, Chunrui Zhang. A neural network model for goat gait[J]. Mathematical Biosciences and Engineering, 2024, 21(8): 6898-6914. doi: 10.3934/mbe.2024302

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Abstract

In this paper, our main objective was to investigate the central pattern generator (CPG) neural network model for quadruped gait with time delay. First, we computed the normal form of the model on the center manifold, the bifurcation direction, and stability conditions of the bifurcating periodic solutions. Second, we applied the CPG model for quadruped gait to obtain reference models for goat's diagonal trotting gait on the flat ground and walking gait on the 18 degree slope through the trust region inversion algorithm. Finally, we performed numerical simulations to support theoretical analysis.

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