System outputs with different sampling times may challenge traditional subspace identification methods to generate accurate process models and consequently provide model-based control systems that may not be very effective. The multi-rate identification problem is addressed by dividing the multi-rate sampled system into different subsystems, and a multi-rate distributed model predictive control technique is proposed to control such systems. The performance of the proposed method is evaluated and illustrated by modeling and controlling the Tennessee Eastman challenge problem.