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The paper presents the modeling and control design of an electromechanical heavy-duty clutch actuator using gain-scheduled MPC and grid-based Linear Parameter Varying approaches. First, the nonlinear model of the electromechanical actuator is presented, then a third order quasi-Linear Parameter Varying representation of the system is derived, which takes the nonlinear characteristic of the diaphragm spring into account. Using the control-oriented model, a Linear Parameter Varying controller and a gain-scheduled Model Predictive Controller are designed, the latter of which serves as benchmark. The controllers have been implemented and tested in a model in the loop environment, where their performances have been compared concerning their rise-time, steady-state error, over-and undershoots, and robustness to the changes of the touch-point. The validation results show that the difference between the model predictive controllers is negligible in most cases, and they surpass the linear parameter varying controller regarding the rise-time. On the other hand, the linear parameter varying approach has proven to be much more robust to the load force and the touch-point changes while also performing better concerning the under- and overshoots. Therefore, it is more suitable to achieve the position control of the actuator.

Quasi-Linear Parameter Varying Modeling and Control of an Electromechanical Clutch Actuator