Five-Link Biped Robot Hybrid Control via Fuzzy Neural Networks
Abstract：The paper presents a new fuzzy neural networks (FNN) hybrid controller to solve the trajectory tracking problem of biped robots in the single-support phase. The advantages of fuzzy neural network, H∞ controller and inverse system method are integrated in this paper for control purpose. A new multi-layers fuzzy CMAC is applied to approximate the system information of biped robot . On the one hand, we regard construction errors of FNN as external disturbances, and then use H∞controller to attenuate such disturbances. On the other hand, apply the strong approximate capability of FNN to construct the inverse system and offer efficient system information to H∞ controller. As the result, L2 gain can be attenuated by the presented fuzzy neural network structure and adaptive algorithm.
Keywords：robotic controlhybrid controlFNNrobust controlinverse system method
Publication Date：2002-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 340-344 )