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Adaptive Linear Quadratic Control for High Dynamical and Comfortable Behavior of a Heavy Truck
- Lena Webersinke - Institute of Industrial Information Technology, Universität Karlsruhe (TH), Germany ,
- Lutz Augenstein - Institute of Industrial Information Technology, Universität Karlsruhe (TH), Germany ,
- Uwe Kiencke - Institute of Industrial Information Technology, Universität Karlsruhe (TH), Germany ,
- Mario Hertweck - Daimler AG, Germany
ISSN: 1946-391X, e-ISSN: 1946-3928
Published April 14, 2008 by SAE International in United States
Citation: Webersinke, L., Augenstein, L., Kiencke, U., and Hertweck, M., "Adaptive Linear Quadratic Control for High Dynamical and Comfortable Behavior of a Heavy Truck," SAE Int. J. Commer. Veh. 1(1):17-24, 2009, https://doi.org/10.4271/2008-01-0534.
During the last few years numerous innovations in advanced driveline control have improved the performance of commercial vehicles. In this context a major goal of driveline control is the enhancement of dynamical behavior and driving comfort. However, fast engine torque changes during Tipin and Tipout operations improve the dynamical behavior but induce unintentional driveline jerking at the same time. Due to this fact that comfort is contradictory to dynamic, a control strategy is necessary, which can handle with both targets at the same time. Based on a simple model of the driveline two Linear Quadratic (LQ) controllers are developed: A comfort controller, which damps the driveline oscillations, and a dynamic controller, which guarantees a high dynamical performance. However, as both controllers have different targets it is not possible to activate both at the same time. Therefore, a fusion of both manipulated variables dependant on the driving situation and the drive input is integrated.
The second main focus of this article is on the problem of dealing with time varying parameters. Adapting the LQ-controllers to these changes by an online identification method based on recursive least-squares estimation is indispensable for a good performance.
Both resulting algorithms - the offline and the online advanced LQ-controllers - are validated in simulation and show a very good improvement of the dynamical behavior as well as the driving comfort at the same time.