Mechanical feedback in nature is a useful concept proposed by many researchers in different areas of biological research. The concept, at its core, is simply the idea that many mechanical processes in biology effectively act to assist in the self-stabilization of tasks, and therefore, serve functionally as a first level of feedback control. However, due to a conventional view of the nervous system as the 'controller' of the body, it has historically been assumed that the control of tasks does not critically depend on the self-stability properties of the mechanical (musculo-skeletal) system. More recent biological research has provided many examples that show neural feedback alone is not sufficient to control many tasks. This forces us to reframe our conventional view of feedback control in neuro-mechanical systems, and by extension, provide a more appropriate perspective when designing biologically-inspired system architectures. Here two ways of diagraming neuro-mechanical control are compared to understand whether one may be more helpful in framing neuro-mechanical control problems and biologically-inspired system design for engineering practitioners and students. This work, when developed further, is expected to provide new pedagogical frameworks for teaching neuromechanics, motor-control, and biologically-inspired methods of control. motor tasks [1-5]. Because high-gain neural feedback tends to destabilize when significant time delays are present, such systems are gain-limited. For this reason, under many circumstances like highly dynamic tasks, neural feedback alone would tend to not have enough 'affordance' to stabilize a desired task. To compensate, a strategy of neural feedforward control and 'mechanical feedback' (self-stabilizing plant dynamics) are utilized.
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