论文标题
非线性生物启发系统的Lyapunov稳定性，用于控制人形生物平衡
Lyapunov Stability of a Nonlinear Bio-inspired System for the Control of Humanoid Balance
论文作者
论文摘要
人体姿势控制模型用于分析人形机器人的神经系统实验和控制。这项工作着重于众所周知的非线性姿势控制模型，即DEC（干扰估计和补偿）。为了补偿干扰，与其他模型不同，来自传感器融合而不是原始感官信号的DECACKACKACK BACKACT信号。在以前的工作中，DEC模型被证明可以预测人类行为并为人形生物提供控制系统。在这项工作中，正式分析了Lyapunov意义上系统的稳定性。理论发现与模拟结果结合使用，其中支撑表面的外部扰动再现了姿势控制实验中的典型情况。
Human posture control models are used to analyse neurological experiments and control of humanoid robots. This work focuses on a well-known nonlinear posture control model, the DEC (Disturbance estimate and Compensation). In order to compensate disturbances, unlike other models, DEC feedbacks signals coming from sensor fusion rather than raw sensory signals. In previous works, the DEC model is shown to predict human behavior and to provide a control system for humanoids. In this work, the stability of the system in the sense of Lyapunov is formally analysed. The theoretical findings are combined with simulation results, in which an external perturbation of the support surface reproduces a typical scenario in posture control experiments.
