Computation of muscle excitation patterns that produce coordinated
movements of muscle-actuated dynamic models is an important and challenging
problem. Using dynamic optimization to compute excitation patterns
comes at a large computational cost, which has limited the use of
muscle-actuated simulations. We have developed a new algorithm, which
we call computed muscle control, that uses static optimization along
with feedforward and feedback controls to drive the kinematic trajectory
of a musculoskeletal model toward a set of desired kinematics.