  Motor control is a fundamental process that underlies all voluntary
behavioral responses. Several different theories based on different principles
(task dynamics, equilibrium-point theory, passive-motion paradigm, active
inference, optimal control) account for specific aspects of how actions are
produced, but fail to provide a unified view on this problem. Here we propose a
concise theory of motor control based on three principles: optimal feedback
control, control with a receding time horizon, and task representation by a
series of via-points updated at fixed frequency. By construction, the theory
provides a suitable solution to the degrees-of-freedom problem, i.e. trajectory
formation in the presence of redundancies and noise. We show through computer
simulations that the theory also explains the production of discrete,
continuous, rhythmic and temporally-constrained movements, and their parametric
and statistical properties (scaling laws, power laws, speed/accuracy
tradeoffs). The theory has no free parameters and only limited variations in
its implementation details and in the nature of noise are necessary to
guarantee its explanatory power.
