An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong ...An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.展开更多
HuR(ELAV11(embryonic lethal,abnormal vision)-like 1),a ubiquitously expressed member of the ELAV-like RNA-binding protein family,has been shown to regulate the stability and translation of mRNAs that encode factors re...HuR(ELAV11(embryonic lethal,abnormal vision)-like 1),a ubiquitously expressed member of the ELAV-like RNA-binding protein family,has been shown to regulate the stability and translation of mRNAs that encode factors regulating cellular senescence,thereby impacting on aging.In this review,we discuss the current knowledge of HuR’s role in vascular cell senescence and vascular aging.展开更多
基金Supported by the National Creative Research Groups Science Foundation of China （60721062） and the National High Technology Research and Development Program of China （2007AA04Z162）.
文摘An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.
基金supported by the National Natural Science Foundation of China(81230008,91339114)111 project of Ministry of Education of China(B07001)
文摘HuR(ELAV11(embryonic lethal,abnormal vision)-like 1),a ubiquitously expressed member of the ELAV-like RNA-binding protein family,has been shown to regulate the stability and translation of mRNAs that encode factors regulating cellular senescence,thereby impacting on aging.In this review,we discuss the current knowledge of HuR’s role in vascular cell senescence and vascular aging.
