TY - GEN
T1 - PCA-based linear parameter varying control of SCR aftertreatment systems
AU - Meisami-Azad, Mona
AU - Mohammadpour, Javad
AU - Grigoriadis, Karolos M.
AU - Harold, Michael P.
AU - Franchek, Matthew A.
PY - 2011
Y1 - 2011
N2 - Hydrocarbons, carbon monoxide, and other polluting emissions produced by diesel engines are usually much lower than those by gasoline engines. However, higher combustion temperature in diesel engines cause substantially larger percentage of nitrogen oxides (NOx) emissions. Selective catalytic reduction (SCR) is a well proven technology for reducing NOx emissions from automotive sources and in particular, heavy-duty diesel engines. In this paper, we develop a quasi linear parameter varying (qLPV) model to capture the nonlinearities in the dynamics of the ammonia SCR system with varying catalyst surface temperature. To effectively enable the use of LMI-based control design methods, the number of LPV parameters in the qLPV model is then reduced by using the principal component analysis (PCA) technique. An LPV feedback/feedforward controller is designed for the qLPV model with reduced number of scheduling parameters. The designed full-order controller is further simplified to a first-order transfer function with parameter-varying gain and pole. Finally, simulation results illustrate the high conversion efficiency with minimum ammonia slip of the closed-loop SCR system using the parameter-varying control law.
AB - Hydrocarbons, carbon monoxide, and other polluting emissions produced by diesel engines are usually much lower than those by gasoline engines. However, higher combustion temperature in diesel engines cause substantially larger percentage of nitrogen oxides (NOx) emissions. Selective catalytic reduction (SCR) is a well proven technology for reducing NOx emissions from automotive sources and in particular, heavy-duty diesel engines. In this paper, we develop a quasi linear parameter varying (qLPV) model to capture the nonlinearities in the dynamics of the ammonia SCR system with varying catalyst surface temperature. To effectively enable the use of LMI-based control design methods, the number of LPV parameters in the qLPV model is then reduced by using the principal component analysis (PCA) technique. An LPV feedback/feedforward controller is designed for the qLPV model with reduced number of scheduling parameters. The designed full-order controller is further simplified to a first-order transfer function with parameter-varying gain and pole. Finally, simulation results illustrate the high conversion efficiency with minimum ammonia slip of the closed-loop SCR system using the parameter-varying control law.
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U2 - 10.1109/acc.2011.5991102
DO - 10.1109/acc.2011.5991102
M3 - Conference contribution
AN - SCOPUS:80053138935
SN - 9781457700804
T3 - Proceedings of the American Control Conference
SP - 1543
EP - 1548
BT - Proceedings of the 2011 American Control Conference, ACC 2011
PB - Institute of Electrical and Electronics Engineers Inc.
ER -