论文信息 - An adaptive iterative learning control scheme for reducing CO2 emission in gasoline engines

An adaptive iterative learning control scheme for reducing CO2 emission in gasoline engines

This paper proposes a control algorithm for a Toyota gasoline engine problem that is addressed in a student competition format. The control objective is to minimize the fuel consumption while avoiding specified dangerous situations. The approach develops a feed-forward control based on an adaptive Iterative Learning Control. In this method, the plant is run several times and the controller iteratively updates the actuation inputs in order to generate the desired reference torque profile. The algorithm converges after approximately 10 iterations providing the corresponding locally optimal control trajectories.

Roy S. Smith | Amin Rezaeizadeh | Roy S. Smith | A. Rezaeizadeh

[1] Lars Eriksson,et al. Modeling and Control of Engines and Drivelines: Eriksson/Modeling and Control of Engines and Drivelines , 2014 .

[2] Roy S. Smith,et al. PULSE COMPRESSOR PHASE AND AMPLITUDE MODULATION BASED ON ITERATIVE LEARNING CONTROL , 2015 .

[3] John B. Heywood,et al. Internal combustion engine fundamentals , 1988 .

[4] Lars Eriksson,et al. Modeling and Control of Engines and Drivelines , 2014 .

[5] Lino Guzzella,et al. Introduction to Modeling and Control of Internal Combustion Engine Systems , 2004 .

[6] Masaru Uchiyama,et al. Formation of High-Speed Motion Pattern of a Mechanical Arm by Trial , 1978 .

[7] Roy S. Smith,et al. RF pulse flattening in the SwissFEL facility based on model-free iterative learning control , 2014 .

[8] E. Rogers,et al. Iterative learning control using optimal feedback and feedforward actions , 1996 .

[9] Stephen P. Boyd,et al. Graph Implementations for Nonsmooth Convex Programs , 2008, Recent Advances in Learning and Control.