Title :
Adaptive optimal control of starting-up of automated manual transmission
Author :
Bin Wang ; Bingzhao Gao ; Hong Chen
Author_Institution :
State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
Abstract :
An adaptive optimal control algorithm based on LQR theory is designed for the automated manual transmission vehicle starting up. The control strategy uses a reduced-order observer of driveline system to estimate the error caused by changes of vehicle parameters. With the estimated modeling error, the optimal control law can engage the clutch rapidly and smoothly when the work condition of the driveline system changes. Through the simulink-AMESim joint simulations on a mid-size passenger car (BESTURN B50 of FAW, China), it is proved that the proposed control strategy can complete the starting-up of the car with satisfied performance even when it´s parameters changes.
Keywords :
adaptive control; automobiles; clutches; digital simulation; linear quadratic control; mechanical engineering computing; observers; power transmission (mechanical); reduced order systems; BESTURN B50; China; FAW; LQR theory; adaptive optimal control; automated manual transmission vehicle starting up; clutch; driveline system; mid-size passenger car; reduced-order observer; simulink-AMESim joint simulations; vehicle parameters; Engines; Friction; Mathematical model; Observers; Optimal control; Torque; Vehicles; Adaptive optimal control; Automated manual transmission; Reduced-order observer;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7052980
