漂浮基双臂空间机器人系统的模糊神经网络自学习控制

Fuzzy Neural Network Self-learning Control of Free-Floating Dual-arm Space Robot System

  • 摘要: 讨论了载体位置、姿态均不受控制的情况下自由漂浮双臂空间机器人系统的高斯基模糊神经网络自学习控制问题.此类空间机器人系统严格遵守动量守恒和角动量守恒,所以其动力学方程表现出强烈的非线性性质.将神经网络与模糊控制相结合,即利用神经网络进行模糊推理,可使模糊控制具有自学习能力.在此基础上,设计了双臂空间机器人系统关节空间的高斯基模糊神经网络自学习控制方案.系统的数值仿真证实了该方法的有效性.

     

    Abstract: Under the condition that the base position and attitude of the free-floating dual-arm space robot system are uncontrolled,the self-learning control problem based on fuzzy Gaussian function neural network is addressed.Since this space robot strictly abide by the rules of momentum conservation and angular momentum conservation,its dynamic equations exhibit a strong nonlinearity.When fuzzy control and neural network are combined,i.e.,the fuzzy inference is realized by neural network,the fuzzy control obtains its self-learning ability.Then the self-learning control scheme based on fuzzy Gaussian function neural network is designed for the dual-arm space robot system in joint space.Numerical simulation is carried out,and the effectiveness of the proposed method is validated.

     

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