Cadence or stride frequency is an important parameter being controlled in gait training of neurologically impaired subjects. The aim of this study was to examine the effects of cadence variation on muscle activation patterns during robot-assisted unimpaired gait using dynamic simulations. A 2-D musculoskeletal model of human gait was developed considering eight major muscle groups along with an existing ground contact force model. A 2-D model of a robotic orthosis was also developed that provides actuation to the hip, knee, and ankle joints in the sagittal plane to guide subject's limbs on reference trajectories. A custom inverse dynamics algorithm was used along with a quadratic minimization algorithm to obtain a feasible set of muscle activation patterns. Predicted patterns of muscle activations during slow, natural, and fast cadence were compared and the mean muscle activations were found to be increasing with an increase in cadence. The proposed dynamic simulation provides important insight into the muscle activation variations with change in cadence during robot-assisted gait and provides the basis for investigating the influence of cadence regulation on neuromuscular parameters of interest during robot-assisted gait.