Stroeve S
Man-Machine Systems and Control Group, Department of Mechanical Engineering, Delft University of Technology, The Netherlands.
Acta Psychol (Amst). 1998 Nov;100(1-2):117-31. doi: 10.1016/s0001-6918(98)00029-8.
A neuromusculoskeletal model of the human arm was developed which contains both feedforward and feedback control, and thereby accounts for motor control of fast movements as well as interaction with external forces. The feedforward control component forms an approximate representation of the inverse dynamics of the arm and its interaction with the environment. The feedback control component compensates for errors in the representation of the inverse dynamics and for unexpected forces acting on the arm. Moreover, the control system provides a solution for the redundancy of the muscles. The system performance is adapted in a learning procedure according to a specified goal function. It is shown in the paper that good control of the nonlinear musculoskeletal model and neural control signals which are similar to electromyographic (EMG) data, are attained. The response of the arm to external forces is analysed and compared with experimental data on arm impedance.
开发了一种人类手臂的神经肌肉骨骼模型，该模型包含前馈和反馈控制，从而解释了快速运动的运动控制以及与外力的相互作用。前馈控制组件形成了手臂逆动力学及其与环境相互作用的近似表示。反馈控制组件补偿逆动力学表示中的误差以及作用在手臂上的意外力。此外，该控制系统为肌肉冗余问题提供了一种解决方案。系统性能在学习过程中根据指定的目标函数进行调整。本文表明，该模型能够很好地控制非线性肌肉骨骼模型，并获得与肌电图（EMG）数据相似的神经控制信号。分析了手臂对外力的响应，并与手臂阻抗的实验数据进行了比较。
