In this paper, the design process of a new model predictive control (MPC) for force-balancing operation mode of a vibratory Micro-Electro-Mechanical-System (MEMS) gyroscope is investigated. Based on the internal model principle, a robust repetitive MPC is proposed to regulate the gyroscope’s drive mode output to a pre-specified periodic reference signal and to set the sense mode vibration to zero. Owing to the fast dynamics of the MEMS gyroscope, large prediction horizons are required to attain the closed-loop stability as well as tracking objectives. In order to alleviate the computational burden of online optimization within large prediction horizons, a set of orthonormal functions, named Laguerre functions are used to parameterize the system trajectories. Distinguishing features of the proposed control method, for MEMS gyroscope applications, are robustness to large parametric uncertainty, exogenous disturbances/noises and the capability to handle the hard input constraints within an optimal setting. Using a recursive least squares algorithm, on-line estimation of the unknown angular rate and the quadrature error of the force-balanced gyroscope is performed. Through computer simulations, the tracking accuracy of the proposed control method together with the convergence of the parameter estimation algorithm is assessed.