在本研究中，吾人将以类神经网路重现动力小艇在波浪中的运动模式。
In this study, the neural network based represented model of wave induced yacht's motion is investigated.
为解决机构复杂的拟人机器人运动学和动力学问题，提出了基于传统机理结合神经网络的建模方法。
To resolve the kinematics modeling and dynamics modeling of a humanoid robot with complicated machine, a modeling method based on the conventional mechanism combined with neural network is presented.
计算结果与实验测量的比较表明：正向动力学方法可将肢体运动状态、肌肉收缩力、神经控制信号等联系起来，求解人体步态的控制模式。
The results show that forward dynamics theory can model the limb movements, muscular forces and neural control signals to simulate the control of a natural gait.
因此，同时考虑机器人运动学和动力学模型，提出基于神经网络的轨迹跟踪算法，仿真结果表明算法具有较强的鲁棒性。
So, we design a trajectory tracking algorithm based on NNs, considering both kinematic and dynamical model, and the simulation results demonstrate that this algorithm has good robustness.
以六自由度运动平台为研究对象，分析了平台的运动学和动力学问题，采用了CMAC神经网络作为控制器，实现运动轨迹的跟踪。
This paper analyzed the kinematics and dynamics of the 6 DOF platform, and adopted CMAC Neural Networks as controller to realize tailing track.
以六自由度运动平台为研究对象，分析了平台的运动学和动力学问题，采用了CMAC神经网络作为控制器，实现运动轨迹的跟踪。
This paper analyzed the kinematics and dynamics of the 6 DOF platform, and adopted CMAC Neural Networks as controller to realize tailing track.
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