Real-Time Implementation of Model Predictive Multivariable Tracking Control for Hydrostatic Transmissions

This paper presents the design and the implementation of a model predictive control with multiple control inputs for a nonlinear hydrostatic transmission system and aims at an accurate tracking control of desired output trajectories under disturbances and uncertainties. The optimal control design is based on a moving horizon optimization using Newton-Raphson techniques. State variables and system disturbances are reconstructed by an unscented Kalman filter. The proposed control is investigated by simulations and experimentally validated at a dedicated test rig at the Chair of Mechatronics, University of Rostock. The robustness of the proposed control structure is indicated by a high tracking accuracy despite system disturbances and model uncertainty.