This paper presents a control architecture for redundant and compliant robots inspired by the theory of biological motor primitives which are theorised to be the mechanism employed by the central nervous system in tackling the problem of redundancy in motor control. In our framework, inspired by self-organisational principles, the simulated robot is first perturbed by a form of spontaneous motor activity and the resulting state trajectory is utilised to reduce the control dimensionality using proper orthogonal decomposition. Motor primitives are then computed using a method based on singular value decomposition. Controllers for generating reduced dimensional commands to reach desired equilibrium positions in Cartesian space are then presented. The proposed architecture is successfully tested on a simulation of a compliant redundant robotic pendulum platform that uses antagonistically arranged series-elastic actuation.