Title :
Predictive control for air fuel ratio based on adaptive expand particle swarm optimization
Author :
Zhi-xiang Hou ; Yi-hu Wu
Author_Institution :
Changsha Univ. of Sci. & Technol., Changsha
Abstract :
Because the oxygen sensor is installed into the vent-pipe of gasoline engine, the air fuel ratio signal of gasoline engine exists transmission delay, which affects the control accuracy of air fuel ratio if using directive air fuel ratio sensor signal. To overcome air fuel ratio transmission delay affection, a new air fuel ratio predictive control method was provided using adaptive expanded particle optimization in this paper. Particle is refreshed using individual and local extremum in the basic PSO algorithm. To improve the global convergence, particle is refreshed by multi-particle strategy; at the same time, parameter c0 is adaptive adjusted for fast the convergence of PSO algorithm. Applying adaptive expand PSO algorithm optimize the control serial of air fuel ratio in the finite time field, and control system stability proof is presented. The simulation was accomplished using experiment data of HQ495 gasoline engine, and the results show that the predictive control method has better performance and the air fuel ratio error is below 1% if slower throttle change, and the air fuel ratio error is below 2% if faster throttle change during transient condition, which will help to improve the emission of gasoline engine.
Keywords :
internal combustion engines; particle swarm optimisation; predictive control; stability; HQ495 gasoline engine; adaptive expand particle swarm optimization; air fuel ratio; control system stability; oxygen sensor; predictive control; Adaptive control; Control systems; Convergence; Delay; Engines; Fuels; Particle swarm optimization; Petroleum; Predictive control; Programmable control; air fuel ratio; neural networks; particle swarm optimization; predictive control; stability;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593008