Maintaining balance during quiet standing is a challenging task for the neural control mechanisms due to the inherent instabilities involved in the task. The feedback latencies and the lowpass characteristics of skeletal muscle add to the difficulty of regulating postural dynamics in real-time. Inverted-pendulum (IP) type robotic models have served as a popular paradigm to investigate control of postural balance. In this study, an in-depth neuromechanical postural control model is developed from physiological principles. The model comprises a single-segment IP robotic model, Hill-type muscle model, and proprioceptive feedback from the muscle spindle (MS) and golgi tendon organ (GTO). An optimal proportional-integral-derivative (PID) controller is proposed to realize effective postural control amid latencies in sensory feedback. The neural commands for postural stabilization are generated by a time-varying PID controller, tuned using linear quadratic regulator (LQR) principles. Computer simulations are used to assess the efficacy of the tuned PID-LQR controller. Sensitivity analysis of the controlled system shows a delay tolerance of 300ms. Preliminary empirical data in support of the mathematical model were obtained from perturbation experiments. The model response to perturbation torque, measured in terms of the center of mass (COM) excursion in the anterior-posterior (AP) direction, displays a high degree of correlation with the empirical data (\(\rho =0.91\)).

由于任务中固有的不稳定性，在安静站立期间保持平衡对于神经控制机制来说是一项具有挑战性的任务。骨骼肌的反馈延迟和低通特性增加了实时调节姿势动态的难度。倒立摆 (IP) 型机器人模型已成为研究姿势平衡控制的流行范例。在这项研究中，一个深入的神经力学姿势控制模型是从生理学原理发展而来的。该模型包括单段 IP 机器人模型、希尔型肌肉模型以及来自肌梭 (MS) 和高尔基肌腱器官 (GTO) 的本体感受反馈。提出了一种最佳比例积分微分 (PID) 控制器，以在感觉反馈延迟中实现有效的姿势控制。用于姿势稳定的神经命令由时变 PID 控制器生成，使用线性二次调节器 (LQR) 原理进行调整。计算机模拟用于评估调谐 PID-LQR 控制器的功效。受控系统的灵敏度分析显示延迟容限为 300女士。支持数学模型的初步经验数据是从扰动实验中获得的。模型对扰动扭矩的响应，根据前后 (AP) 方向的质心 (COM) 偏移量来衡量，显示出与经验数据 ( \(\rho =0.91\) ) 的高度相关性。