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FUZZY WAVELET CMAC NEURAL NETWORK CONTROL FOR FREE-FLOATING SPACE FLEXIBLE MANIPULATOR TO TRACK DESIRED TRAJECTORY

机译:用于跟踪所需轨迹的自由浮动空间柔性机械手模糊小波CMAC神经网络控制

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Space manipulator system will play more and more important function in future space activities, and its research get the attention of all parties. However, with the development of space technology and continuous improvement of modern robot manufacture technology, late-model space robot will progress in the direction of lightsome, high speed and high precision, and concerned dynamics and control problems on flexible space robot will become the hot topics for people to discuss. The trajectory tracking control for coordinated motion of free-floating space flexible manipulator with unknown parameters is developed. With the law of conservation of momentum, the Lagrange equation of the second kind is utilized to model the dynamic function of the space flexible manipulator incorporating the assumed modes method. Base on above, in case of system parameters are unknown, a fuzzy wavelet CMAC neural network control scheme is designed. The control scheme can control the base attitude and joint angle of manipulator to track desired trajectories in joint space at the same time. The control scheme not only requires no a priori knowledge about the dynamic model and system parameters, but also saves the on-line training time because of the network weights are adjusted through online learning. Simulation result demonstrates the valid and feasible of the proposed control scheme.
机译:空间机械手系统将在未来的空间活动中发挥越来越重要的功能,其研究得到了各方的关注。但是,随着空间技术的发展和现代机器人制造技术的持续改进,晚模空间机器人将在Lights的方向上进步,高速高精度,以及灵活空间机器人的有关动态和控制问题将成为热门人们讨论的主题。开发了具有未知参数的自由浮动空间柔性机械手的协调运动的轨迹跟踪控制。随着动量守恒定律,第二种的拉格朗日方程用于模拟包含假定模式方法的空间柔性机械手的动态功能。如上所述,在系统参数未知的情况下,设计了一种模糊小波CMAC神经网络控制方案。控制方案可以控制操纵器的基本姿态和关节角度,同时在关节空间中跟踪所需的轨迹。控制方案不仅需要关于动态模型和系统参数的先验知识,而且还可以通过在线学习调整网络权重,节省在线培训时间。仿真结果展示了所提出的控制方案的有效和可行性。

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