Five-Link Biped Robot Hybrid Control via Fuzzy Neural Networks
基于模糊神经网络的5连杆双足机器人混杂控制（英文）

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-infinity 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-infinity 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-infinity controller. As the result, L-2 gain can be attenuated by the presented fuzzy neural network structure and adaptive algorithm.