A key problem for biological motor control is to establish a link between an idea of a movement and the generation of a set of muscle-stimulating signals that lead to the movement execution. The number of signals to generate is thereby larger than the body’s mechanical degrees of freedom in which the idea of the movement may be easily expressed, as the movement is actually executed in this space. A mathematical formulation that provides a solving link is presented in this paper in the form of a layered, hierarchical control architecture. It is meant to synthesise a wide range of complex three-dimensional muscle-driven movements. The control architecture consists of a ‘conceptional layer’, where the movement is planned, a ‘structural layer’, where the muscles are stimulated, and between both an additional ‘transformational layer’, where the muscle-joint redundancy is resolved. We demonstrate the operativeness by simulating human stance and squatting in a three-dimensional digital human model (DHM). The DHM considers 20 angular DoFs and 36 Hill-type muscle–tendon units (MTUs) and is exposed to gravity, while its feet contact the ground via reversible stick–slip interactions. The control architecture continuously stimulates all MTUs (‘structural layer’) based on a high-level, torque-based task formulation within its ‘conceptional layer’. Desired states of joint angles (postural plan) are fed to two mid-level joint controllers in the ‘transformational layer’. The ‘transformational layer’ communicates with the biophysical structures in the ‘structural layer’ by providing direct MTU stimulation contributions and further input signals for low-level MTU controllers. Thereby, the redundancy of the MTU stimulations with respect to the joint angles is resolved, i.e. a link between plan and execution is established, by exploiting some properties of the biophysical structures modelled. The resulting joint torques generated by the MTUs via their moment arms are fed back to the conceptional layer, closing the high-level control loop. Within our mathematical formulations of the Jacobian matrix-based layer transformations, we identify the crucial information for the redundancy solution to be the muscle moment arms, the stiffness relations of muscle and tendon tissue within the muscle model, and the length–stimulation relation of the muscle activation dynamics. The present control architecture allows the straightforward feeding of conceptional movement task formulations to MTUs. With this approach, the problem of movement planning is eased, as solely the mechanical system has to be considered in the conceptional plan.

生物运动控制的一个关键问题是在运动的概念和导致运动执行的一组肌肉刺激信号的产生之间建立联系。从而产生的信号数量大于身体的机械自由度，在该自由度中运动的想法可以很容易地表达，因为运动实际上是在这个空间中执行的。本文以分层、分层控制架构的形式提供了一个数学公式，该公式提供了一个求解链接。它旨在综合各种复杂的三维肌肉驱动运动。控制架构由一个“概念层”组成，其中计划运动，一个“结构层”，肌肉受到刺激，以及两个额外的“转换层”之间，在那里解决了肌肉关节冗余。我们通过在三维数字人体模型 (DHM) 中模拟人体姿势和蹲下来证明其可操作性。DHM 考虑了 20 个角自由度和 36 个希尔型肌肉 - 肌腱单位 (MTU) 并受到重力的影响，而其脚通过可逆的粘滑相互作用接触地面。控制架构基于其“概念层”内的高级、基于扭矩的任务公式不断刺激所有 MTU（“结构层”）。所需的关节角度状态（姿势计划）被馈送到“转换层”中的两个中级关节控制器。“转换层”通过为低级 MTU 控制器提供直接的 MTU 刺激贡献和进一步的输入信号，与“结构层”中的生物物理结构进行通信。从而，通过利用建模的生物物理结构的一些特性，解决了关于关节角度的 MTU 刺激的冗余，即建立了计划和执行之间的联系。MTU 通过它们的力臂产生的最终关节扭矩被反馈到概念层，从而关闭高级控制回路。在我们基于 Jacobian 矩阵的层变换的数学公式中，我们确定了冗余解决方案的关键信息是肌肉力臂、肌肉模型中肌肉和肌腱组织的刚度关系以及长度-刺激关系肌肉激活动力学。当前的控制架构允许将概念运动任务公式直接提供给 MTU。通过这种方法，