An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.
研究柔性冗余度机器人的残余振动主动控制问题。设计了具有压电作动器与应变传感器的机敏杆件 ,建立了受控系统的状态空间表达式。采用独立模态空间控制理论设计 L QR状态反馈控制器 ,并基于对偶原理设计了具有指定收敛特性的 L uenberger全维状态观测器。最后 ,以平面 3R柔性冗余度机器人为例进行了计算机仿真。结果表明 ,采用这种主动控制方法可以显著改善柔性冗余度机器人的动力学品质。
