  Nonlinear control methodologies have successfully realized stable human-like
walking on powered prostheses. However, these methods are typically restricted
to model independent controllers due to the unknown human dynamics acting on
the prosthesis. This paper overcomes this restriction by introducing the notion
of a separable subsystem control law, independent of the full system dynamics.
By constructing an equivalent subsystem, we calculate the control law with
local information. We build a subsystem model of a general open-chain
manipulator to demonstrate the control method's applicability. Employing these
methods for an amputee-prosthesis model, we develop a model dependent
prosthesis controller that relies solely on measurable states and inputs but is
equivalent to a controller developed with knowledge of the human dynamics and
states. We demonstrate the results through simulating an amputee-prosthesis
system and show the model dependent prosthesis controller performs identically
to a feedback linearizing controller based on the whole system, confirming the
equivalency.
