Optimized Pole Placement Control For Air-Fuel Ratio Based On Particle Swarm Optimization

The incomplete combustion of the fuel from gasoline engine will cause environmental pollution and energy waste,which makes its economy and emission performance degradation.By using the three-way catalytic converter,gasoline engine can reduce harmful gas,but its most effective transformation requires air quality and fuel quality mixing ratio(air-fuel ratio,AFR)to remain near the desired value.The traditional AFR control method is based on the MAP(manifold air pressure)with PI method,which is easy to calculate.But this method required a large number of calibration tests,and the accuracy is not high in the transient conditions.Therefore,the design of an AFR controller with simple structure and high control accuracy is of great importance.On the basis of summing up the AFR control technology of gasoline engine,this dissertation proposes a new control method with applying the mean value engine model(EMVM),Particle Swarm Optimization(Particle Swarm Optimization,PSO)and pole placement control technology,which realizes the precise AFR control of gasoline engine.The main achievements and innovations of this dissertation are as follows:(1)The optimized pole placement of the Linear Time-invariant System is proposed,and the state feedback and output feedback controller is designed for the optimal pole assignment.The PSO algorithm is adopted to solve problem how to optimize pole placement control for AFR based on the EMVM of gasoline engine,and realizes the design of the state feedback controller by the optimized pole placemengt;Further considering that the state of the AFR system is not a direct measurement,this paper introduces a state observer to reconstruct the state of the system,thus to realizes the design of the output feedback controller by the optimized pole placemengt based on the observer.Finally,the effectiveness of the AFR controller is verified by numerical simulation.(2)A new Genetic Particle Swarm Optimization is improved and obtained,and the tracking controller is designed by the optimized pole placement for the AFR of gasoline engine.Aiming at the problem of PSO algorithm which is easy to get into local optimal location,a modified Genetic and Particle Swarm Optimization(Modified Genetic Particle Swarm Optimization,MGPSO)algorithm is proposed which combines with the crossover and mutation of Genetic algorithm,and introduces the average optimal location.Poles of the system and observer are optimized simultaneously based on MGPSO algorithm,and to realize the AFR tracking control with zero static error.Finally,the effectiveness of the AFR controller is verified by numerical simulation.