Biological motor control provides highly effective solutions to difficult
control problems in spite of the complexity of the plant and the significant
delays in sensory feedback . Such delays are expected to lead to non trivial
stability issues and lack of robustness of control solutions. However, such
difficulties are not observed in biological systems under normal operating
conditions. Based on early suggestions in the control literature, a possible
solution to this conundrum has been the suggestion that the motor system
contains within itself a forward model of the plant (e.g., the arm), which
allows the system to `simulate' and predict the effect of applying a control
signal. In this work we formally define the notion of a forward model for
deterministic control problems, and provide simple conditions that imply its
existence for tasks involving delayed feedback control. As opposed to previous
work which dealt mostly with linear plants and quadratic cost functions, our
results apply to rather generic control systems, showing that any controller
(biological or otherwise) which solves a set of tasks, \emph{must} contain
within itself a forward plant model. We suggest that our results provide strong
theoretical support for the necessity of forward models in many delayed control
problems, implying that they are not only useful, but rather, mandatory, under
general conditions.