@ARTICLE{Soltani_Abbas_Application_2022,
 author={Soltani, Abbas and Arianfard, Milad and Jazar, Reza Nakhaie},
 volume={vol. 69},
 number={No 2},
 journal={Archive of Mechanical Engineering},
 pages={319-339},
 howpublished={online},
 year={2022},
 publisher={Polish Academy of Sciences, Committee on Machine Building},
 abstract={In this paper, an adaptive sliding mode controller (ASMC) is proposed for an electromechanical clutch position control system to apply in the automated manual transmission. Transmission systems undergo changes in parameters with respect to the wide range of driving condition, such as changing in friction coefficient of clutch disc and stiffness of diaphragm spring, hence, an adaptive robust control method is required to guarantee system stability and overcome the uncertainties and disturbances. As the majority of transmission dynamics variables cannot be measured in a cost-efficient way, a non-linear estimator based on unscented Kalman filter (UKF) is designed to estimate the state valuables of the system. Also, a non-linear dynamic model of the electromechanical actuator is presented for the automated clutch system. The model is validated with experimental test results. Numerical simulation of a reference input for clutch bearing displacement is performed in computer simulation to evaluate the performance of controller and estimator. The results demonstrate the high effectiveness of the proposed controller against the conventional sliding mode controller to track precisely the desired trajectories.},
 type={Article},
 title={Application of unscented Kalman filter for clutch position control of automated manual transmission},
 URL={http://journals.pan.pl/Content/122955/PDF/AME_2022_140418.pdf},
 doi={10.24425/ame.2022.140418},
 keywords={automated clutch, actuator, adaptive sliding mode control, estimator, unscented Kalman filter},
}