Neuronal circuits known as central pattern generators (CPG) are responsible for the rhythmic motions in animal locomotion. These circuits exploit the resonant modes of the body to produce efficient locomotion through sensory feedback. As such, the neuronal mechanisms are of interest in the control of autonomous robotic vehicles. The objective of this study is to establish a design framework that integrates synthesized CPGs with tensegrity structures, with the goal of resonance entrainment. Tensegrities are novel, nonlinear dynamic structures featuring high strength to weight ratios, embedded actuation and sensing, and tunable stiffness. A two-neuron circuit known as a reciprocal inhibition oscillator is integrated with tensegrity structures with a pair of antagonistic actuators and collocated sensors. Each neuron has control of a cable length, and the sensory signal of cable length is fed back to the neuron. The frequency and amplitude of closed-loop oscillation are analyzed via harmonic balance, and a systematic method for control design is proposed to achieve entrainment to a prescribed resonance mode. Published by Elsevier Ltd