Title :
Model predictive control based on observer for engine idle speed control
Author :
Shu, Li ; Yanzhi, Li ; Yunfeng, Hu ; Xingwen, Dong
Author_Institution :
Air Force Aviation Univ., China
Abstract :
Idle speed control of engine is always one of the most important automotive control problems. And the closed-loop control using advanced control methodologies is well-suited for idle speed control problem. In this paper, a controller using linear model predictive control (MPC) methodology based on observer is designed to regulate the engine speed at a reference speed. The state variable with high measurement noise is estimated by Kalman filter in engine system. Therefore, the engine idle speed control comes down to optimization problem with input and state constraints. The simulation results show that the approach is an effective and promising for the engine idle speed control.
Keywords :
Kalman filters; angular velocity control; closed loop systems; control system synthesis; internal combustion engines; linear systems; observers; optimisation; predictive control; Kalman filter; automotive control problem; closed loop control; engine idle speed control; engine speed regulation; linear model predictive control; measurement noise; observer-based controller design; optimization; state constraint; state variable estimation; Engines; Manifolds; Noise; Noise measurement; Sparks; Torque; Velocity control; Engine idle speed control; Kalman filter; Model predictive control; Quadratic program;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3