摘要
针对含有动态摩擦的可重构机械臂轨迹跟踪执行器部分失效故障的问题,提出一种基于有效因子融合的分散反演滑模容错控制方法。将可重构机械臂的每个关节模块考虑成一个子系统,将有效因子融合到子系统动力学模型中。基于Lyapunov稳定性理论,子系统误差状态空间分别采用了反演思想和终端滑模进行控制器设计,并利用径向基函数(RBF)神经网络估计系统模型的不确定项和交联项,自适应地补偿了神经网络的估计误差。最后,数值仿真结果表明了提出的分散容错方法的有效性。
A decentralized backstepping sliding mode fault tolerant scheme was developed to prevent partial loss of actuator effectiveness of reeonfigurable manipulators with dynamic friction. An effectiveness factor was integrated into the dynamic model of each module subsystem of the reeonfigurahle manipulators. Lyapunov stability theory was used to develop backstepping and terminal sliding techniques for controller design in subsystem state error space. The radial basis function (RBF) neural networks, uncertainty terms and interconnection terms were estimated with adaptive compensation of the estimation error. Simulations show the effectiveness of this decentralized fault tolerant scheme.
出处
《清华大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2012年第9期1218-1222,1229,共6页
Journal of Tsinghua University(Science and Technology)
基金
国家自然科学基金面上项目(60974010
60674091)
吉林省科技发展计划项目(20110705)
关键词
可重构机械臂
容错控制
有效因子融合
部分失效故障
反演滑模
reconfigurable manipulators
fault tolerant control
effective factor integration
partial loss of actuator effectiveness
hackstepping sliding mode