Nonlinear Model-Predictive Control of an Electro-Pneumatic Clutch for Truck Applications

This paper presents a nonlinear model predictive control design for an electropneumatic clutch for heavy trucks, which is required at start-up or during gear shifts to disconnect the combustion engine from the gear box. This automated actuator disburdens the driver and provides the necessary actuation force according to the large torque transmitted through the powertrain. The main idea of the used NMPC algorithm consists in a minimisation of the tracking error at the end of the prediction horizon. That way the computation load can be kept relatively small. A reduced-order disturbance observer estimates the internal pressure, which is usually not measured in truck applications. Thereby, high tracking accuracy is achievable for the piston position as controlled variable. The efficiency of the proposed control structure is emphasised by experimental results from a dedicated test rig.