Fuzzy Neural Network Hybrid Learning Control on AUV

Jing Zhao; Zhao Lin Han; Yuan Yuan Fang

doi:10.4028/www.scientific.net/AMR.468-471.1732

Paper Titles

Study of the Control of Active Transfemoral Prosthesis Based on CPG
p.1710

Forecasting the Exchange Rate Using the Improved SAPSO Neural Network
p.1714

The Design and Implementation of a High-Speed Parallel AES Crypto-Chip
p.1721

First-Principles Conductance Calculations of Ag-Al Co-Doped ZnO
p.1726

Fuzzy Neural Network Hybrid Learning Control on AUV
p.1732

Fluctuating Pressure Calculation during the Progress of Trip in Managed Pressure Drilling
p.1736

Fault Diagnosis of Elevator Based AR Bi-Spectrum
p.1743

Flow Field Analysis of Conducting Trunk of Comb-Type Cotton Picker
p.1749

Fire Hazard Factors of Residential-Commercial Composite Buildings through Fire Hazard Cases
p.1753

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Fuzzy Neural Network Hybrid Learning Control on...

Fuzzy Neural Network Hybrid Learning Control on AUV

Abstract:

A novel controller based on the fuzzy B-spline neural network is presented, which combines the advantages of qualitative defining capability of fuzzy logic, quantitative learning ability of neural networks and excellent local controlling ability of B-spline basis functions, which are being used as fuzzy functions. A hybrid learning algorithm of the controller is proposed as well. The results show that it is feasible to design the fuzzy neural network control of autonomous underwater vehicle by the hybrid learning algorithm.