摘要
基于小波神经网络,提出了一种新的受时变约束机器人力/位置控制算法。由系统约束关系推导了降阶的动力学模型,基于降阶模型设计了鲁棒小波神经网络力/位置控制算法。由Barbalat给出了系统的稳定性证明。数值仿真结果验证了本文控制算法的有效性。
For rheonomically constrained manipulator systems, a robust position/force control algorithm was designed on the basis of wavelet network for the approximation of nonlinear part and unmodelled dynamics of robotic systems. A compensation term was used to simplify the wavelet network structure, and the control algorithm can guarantee the system robustness and solve force/ position control problem. Theoretical analysis and simulation were carried out to demonstrate the effectiveness of the proposed control method.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2008年第1期163-167,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(60674091)
关键词
自动控制技术
机械臂
力/位置控制
小波神经网络
automatic control technology
manipulator
position/force control
wavelet network
