Title :
RBF neural networks based robot non-smooth adaptive control
Author :
Zhao Dongya ; Zhu Quanmin ; Li Shaoyuan
Author_Institution :
Coll. of Chem. Eng., China Univ. of Pet., Qingdao, China
Abstract :
A novel non-smooth adaptive robot control is proposed in light of general error decimal power law and RBF neural networks. The corresponding stability analysis is presented to lay a foundation to the safe operation in practice. An illustrative example is used to validate the effectiveness of the proposed approach.
Keywords :
adaptive control; neurocontrollers; radial basis function networks; robots; stability; RBF neural networks; general error decimal power law; nonsmooth adaptive robot control; radial basis function networks; stability analysis; Adaptive control; Artificial neural networks; Manipulators; Robot control; Trajectory; Vectors; Non-smooth control; RBF neural networks; adaptive control; robot control;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
