Decentralized Adaptive Neural Network Control for Reconfigurable Manipulators

摘要：

In this paper, a decentralized adaptive neural network control algorithm for reconfigurable manipulators based on Lyapunov’s stability analysis and backstepping techniques is proposed. The dynamics of reconfigurable manipulators is represented as a set of interconnected subsystems. Neural networks are used to approximate the unknown dynamic functions and interconnections in the subsystems by using adaptive algorithm. The effectiveness of the proposed scheme is demonstrated by computer simulations.

关键词： Reconfigurable Manipulators Decentralized Control Neural Networks Adaptive Control Backstepping Design

作者: Lu Zhu Yuanchun Li

作者单位: State Key Laboratory of Automobile Dynamic Simulation, Jilin University, Changchun 130022, China Dep Department of Communication Engineering, Jilin University, Changchun 130022, China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 1760-1765

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）