LPV gain-scheduled control of SCR aftertreatment systems

被引:21
|
作者
Meisami-Azad, Mona [1 ]
Mohammadpour, Javad [1 ]
Grigoriadis, Karolos M. [1 ]
Harold, Michael P. [2 ]
Franchek, Matthew A. [1 ]
机构
[1] Univ Houston, Dept Mech Engn, Houston, TX 77204 USA
[2] Univ Houston, Dept Chem & Biomol Engn, Houston, TX 77204 USA
关键词
selective catalytic reduction; gain-scheduling control; principal component analysis; PARAMETER; MODELS;
D O I
10.1080/00207179.2011.639090
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hydrocarbons, carbon monoxide and some of other polluting emissions produced by diesel engines are usually lower than those produced by gasoline engines. While great strides have been made in the exhaust aftertreatment of vehicular pollutants, the elimination of nitrogen oxide (NOx) from diesel vehicles is still a challenge. The primary reason is that diesel combustion is a fuel-lean process, and hence there is significant unreacted oxygen in the exhaust. Selective catalytic reduction (SCR) is a well-developed technology for power plants and has been recently employed for reducing NOx emissions from automotive sources and in particular, heavy-duty diesel engines. In this article, we develop a linear parameter-varying (LPV) feedforward/feedback control design method for the SCR aftertreatment system to decrease NOx emissions while keeping ammonia slippage to a desired low level downstream the catalyst. The performance of the closed-loop system obtained from the interconnection of the SCR system and the output feedback LPV control strategy is then compared with other control design methods including sliding mode, and observer-based static state-feedback parameter-varying control. To reduce the computational complexity involved in the control design process, the number of LPV parameters in the developed quasi-LPV (qLPV) model is reduced by applying the principal component analysis technique. An LPV feedback/feedforward controller is then 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 a parameter-varying gain and pole. Finally, simulation results using both a low-order model and a high-fidelity and high-order model of SCR reactions in GT-POWER interfaced with MATLAB/SIMULINK illustrate the high NOx conversion efficiency of the closed-loop SCR system using the proposed parameter-varying control law.
引用
收藏
页码:114 / 133
页数:20
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