Title :
Hysteresis compensation and adaptive LQR design for an electro-pneumatic clutch for heavy trucks
Author :
Aschemann, Harald ; Prabel, Robert ; Schindele, D.
Author_Institution :
Dept. of Mechatron., Univ. of Rostock, Rostock, Germany
Abstract :
In this paper, a nonlinear model-based control design for an electro-pneumatic clutch for heavy trucks is presented. A clutch 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. The proposed feedback control represents an adaptive LQR design using extended linearisation techniques, where the controller gains are adapted by solving numerically the corresponding Riccati equation in real-time. In addition, an adaptive feedforward control is designed with the clutch position as controlled variable. The control structure is extended by a reduced-order observer that estimates an effective pressure, which accounts for model uncertainty as well as nonlinear friction. Moreover, an experimentally identified Bouc-Wen hysteresis model is used to improve the dynamic behaviour further. Thereby, high tracking accuracy is achievable for the piston position. The performance of the proposed control structure is pointed out by experimental results from a dedicated test rig.
Keywords :
Riccati equations; adaptive control; clutches; compensation; control nonlinearities; control system synthesis; electropneumatic control equipment; feedback; feedforward; friction; linear quadratic control; linearisation techniques; nonlinear control systems; observers; pistons; reduced order systems; road vehicles; Bouc-Wen hysteresis model; Riccati equation; actuation force; adaptive LQR design; adaptive feedforward control; automated actuator; combustion engine; controller gains; dynamic behaviour; effective pressure; electro-pneumatic clutch; extended linearisation techniques; feedback control; gear box; heavy trucks; hysteresis compensation; model uncertainty; nonlinear friction; nonlinear model-based control design; piston position; reduced-order observer; tracking accuracy; Feedforward neural networks; Force; Hysteresis; Mathematical model; Observers; Pistons; Valves;
Conference_Titel :
Control Conference (ECC), 2013 European
Conference_Location :
Zurich