摘要
ALSTOM气化炉具有强的非线性及大惯性,常规的控制方法难以满足全工况运行条件下的各项控制指标.采用模糊推理方法,将气化炉在多个工况条件下的局部线性模型综合成全局模糊模型,并在此基础上应用预测控制技术,提出了一种新型的基于过程全局模糊模型的模糊增益调度预测控制方法,并应用于气化炉多变量非线性优化控制.仿真结果表明:即使各个输入受到运行条件的严格约束,各个输出变量仍能较好地维持在ALSTOM气化炉所要求的范围内,具有较好的控制品质,为气化炉的全局优化控制提供了一个较好的方法.
Due to its strong non-linearity and large inertia characteristics, ALSTOM gasifier is generally difficult to be controlled with conventional control schemes under all working conditions. Using fuzzy reasoning method, local linear models of gasifier constructed for different operating conditions were first integrated into a global fuzzy model, then a new type of fuzzy gain scheduling model predictive controller based on process and global fuzzy models was proposed and applied to its nonlinear multivariable optimization control. Extensive simulations show that all the outputs can be kept within desired operating boundaries of ALSTOM gasifier while subjecting to corresponding input constraints, demonstrating a good control performance. The way is thus proved to be a good approach for global optimization control of ALSTOM gasifiers.
出处
《动力工程》
EI
CSCD
北大核心
2008年第2期229-237,共9页
Power Engineering
基金
国家863高技术基金资助项目(2006AA05A107)
高校博士点基金资助项目(20050286041)
关键词
自动控制技术
ALSTOM气化炉
模糊模型
预测控制
增益调度
约束
优化
automatic control technique
ALSTOM gasifier
fuzzy model
predictive control
gainscheduling
constraint
optimization
