The Dynamic Matrix Control （DMC） algorithm tor integral processes is investigated in this paper. The reason why the original DMC algorithm cannot be applied to these processes is analyzed. The shifting matrix is tra...The Dynamic Matrix Control （DMC） algorithm tor integral processes is investigated in this paper. The reason why the original DMC algorithm cannot be applied to these processes is analyzed. The shifting matrix is transformed into another form and the corresponding theorem is proved, then its applicable range is extended. Compared with other algorithms on the integral processes, this algorithm is more practical and simple to implement. Simulation results also prove its validity. Applying this algorithm, we succeed in the control of the boiler level system in power units.展开更多
Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivate...Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivated to propose a new monitoring method by compensating the principal component analysis with a weight approach.The proposed monitor consists of two tiers. The first tier uses the principal component analysis method to extract cross-correlation structure among process data, expressed by independent components. The second tier estimates auto-correlation structure among the extracted components as auto-regressive models. It is therefore named a dynamic weighted principal component analysis with hybrid correlation structure. The essential of the proposed method is to incorporate a weight approach into principal component analysis to construct two new subspaces, namely the important component subspace and the residual subspace, and two new statistics are defined to monitor them respectively. Through computing the weight values upon a new observation, the proposed method increases the weights along directions of components that have large estimation errors while reduces the influences of other directions. The rationale behind comes from the observations that the fault information is associated with online estimation errors of auto-regressive models. The proposed monitoring method is exemplified by the Tennessee Eastman process. The monitoring results show that the proposed method outperforms conventional principal component analysis, dynamic principal component analysis and dynamic latent variable.展开更多
Understanding the underlying processes of how communities are structured remains a central question in community ecology. However, the mechanisms of the soil animal community are still unclear, especially for communit...Understanding the underlying processes of how communities are structured remains a central question in community ecology. However, the mechanisms of the soil animal community are still unclear, especially for communities on a small scale. To evaluate the relative roles of biotic interactions and environmental and spatial processes in a soil collembolan community, a field experiment was carried out on a small scale(50 m) in the farmland ecosystem of the Sanjiang Plain, Northeast China. In August and October, 2011, we took 100 samples each month in a 50 m × 50 m plot using a spatially delimited sampling design. Variation partitioning was used to quantify the relative contributions of the spatial and environmental variables. A null model was selected to test for the non-randomness pattern of species co-occurrence and body size in assemblages of collembolans and to test whether the pattern observed was the result of environmental or biotic processes that structured the community on a small scale. The results showed that large variance was accounted for by spatial variables(18.99% in August and 21.83% in October, both were significant). There were relatively lower effects of environmental variation(3.56% in August and 1.45% in October, neither was significant), while the soil water content, soil p H and soybean height explained a significant portion of the variance that was observed in the spatial pattern of the collembolan community. Furthermore, the null model revealed more co-occurrence than expected by chance, suggesting that collembolan communities had a non-random co-occurrence pattern in both August and October. Additionally, environmental niche overlap and the body size ratio of co-occurrence showed that interspecific competition was not influential in collembolan community structuring. Considering all of the results together, the contributions of spatial and environmental processes were stronger than biotic interactions in the small-scale structuring of a soil collembolan community.展开更多
Aims Adaptive convergence in floral phenotype among plants sharing a pollinator guild has been acknowledged in the concept of pollination syndrome.However,many plants display traits associated with a given syndrome,bu...Aims Adaptive convergence in floral phenotype among plants sharing a pollinator guild has been acknowledged in the concept of pollination syndrome.However,many plants display traits associated with a given syndrome,but are visited by multiple pollinators.This situation may indicate the beginning of a pollinator shift or may result in a stable situation with adaptations to different pollinators.In Salvia stachydifolia,a previous study suggested that flower shape is optimized to maximize the contribution to pollination of bees and hummingbirds.Here,we studied three additional aspects of its floral biology:sexual phases,nectar dynamics and breeding system,and examined their connection with pollinators’behaviour to explore the presence of adaptations to bee and/or hummingbird pollination.Methods Using a greenhouse population,we applied five pollination treatments to characterize breeding system.To determine sexual phases,we recorded flower opening,anther dehiscence,corolla fall and stigma receptivity.Additionally,we characterized nectar volume and concentration dynamics along the day.Finally,to determine pollinator assemblage and visitation patterns,we performed field observations and recorded pollinators’behaviour.Important Findings Salvia stachydifolia was partially protandrous and self-compatible,but open-pollinated plants attained the highest reproductive success,suggesting that reproduction is mainly dependent on pollinator activity.Bombus opifex bumblebees were the most frequent visitors,but Sappho sparganura hummingbirds dominated visits early in the morning and at dusk.Nectar was typical of bumblebee pollination.We suggest that the bee–hummingbird mixed visitation constitutes an unstable evolutionary situation,making S.stachydifolia an ideal system to understand the ecological circumstances in which pollination shifts occur.展开更多
文摘The Dynamic Matrix Control （DMC） algorithm tor integral processes is investigated in this paper. The reason why the original DMC algorithm cannot be applied to these processes is analyzed. The shifting matrix is transformed into another form and the corresponding theorem is proved, then its applicable range is extended. Compared with other algorithms on the integral processes, this algorithm is more practical and simple to implement. Simulation results also prove its validity. Applying this algorithm, we succeed in the control of the boiler level system in power units.
基金Supported by the National Natural Science Foundation of China(61174114)the Research Fund for the Doctoral Program of Higher Education in China(20120101130016)+1 种基金the Natural Science Foundation of Zhejiang Province(LQ15F030006)and the Science and Technology Program Project of Zhejiang Province(2015C33033)
文摘Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivated to propose a new monitoring method by compensating the principal component analysis with a weight approach.The proposed monitor consists of two tiers. The first tier uses the principal component analysis method to extract cross-correlation structure among process data, expressed by independent components. The second tier estimates auto-correlation structure among the extracted components as auto-regressive models. It is therefore named a dynamic weighted principal component analysis with hybrid correlation structure. The essential of the proposed method is to incorporate a weight approach into principal component analysis to construct two new subspaces, namely the important component subspace and the residual subspace, and two new statistics are defined to monitor them respectively. Through computing the weight values upon a new observation, the proposed method increases the weights along directions of components that have large estimation errors while reduces the influences of other directions. The rationale behind comes from the observations that the fault information is associated with online estimation errors of auto-regressive models. The proposed monitoring method is exemplified by the Tennessee Eastman process. The monitoring results show that the proposed method outperforms conventional principal component analysis, dynamic principal component analysis and dynamic latent variable.
基金Under the auspices of National Natural Science Foundation of China(No.41101049,41471037,41371072,41430857)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(No.UNPYSCT-2015054)+1 种基金Distinguished Young Scholar of Harbin Normal University(No.KGB201204)Excellent Youth Scholars of Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences(No.DLSYQ13003)
文摘Understanding the underlying processes of how communities are structured remains a central question in community ecology. However, the mechanisms of the soil animal community are still unclear, especially for communities on a small scale. To evaluate the relative roles of biotic interactions and environmental and spatial processes in a soil collembolan community, a field experiment was carried out on a small scale(50 m) in the farmland ecosystem of the Sanjiang Plain, Northeast China. In August and October, 2011, we took 100 samples each month in a 50 m × 50 m plot using a spatially delimited sampling design. Variation partitioning was used to quantify the relative contributions of the spatial and environmental variables. A null model was selected to test for the non-randomness pattern of species co-occurrence and body size in assemblages of collembolans and to test whether the pattern observed was the result of environmental or biotic processes that structured the community on a small scale. The results showed that large variance was accounted for by spatial variables(18.99% in August and 21.83% in October, both were significant). There were relatively lower effects of environmental variation(3.56% in August and 1.45% in October, neither was significant), while the soil water content, soil p H and soybean height explained a significant portion of the variance that was observed in the spatial pattern of the collembolan community. Furthermore, the null model revealed more co-occurrence than expected by chance, suggesting that collembolan communities had a non-random co-occurrence pattern in both August and October. Additionally, environmental niche overlap and the body size ratio of co-occurrence showed that interspecific competition was not influential in collembolan community structuring. Considering all of the results together, the contributions of spatial and environmental processes were stronger than biotic interactions in the small-scale structuring of a soil collembolan community.
基金This study was supported by Fondo para la Investigacion Cientffica y Tecnoldgica(FONCyT)grant PICT 2017-2196 to S.B.V.and by FONCyT grant PICT-2018-03192 to F.S.
文摘Aims Adaptive convergence in floral phenotype among plants sharing a pollinator guild has been acknowledged in the concept of pollination syndrome.However,many plants display traits associated with a given syndrome,but are visited by multiple pollinators.This situation may indicate the beginning of a pollinator shift or may result in a stable situation with adaptations to different pollinators.In Salvia stachydifolia,a previous study suggested that flower shape is optimized to maximize the contribution to pollination of bees and hummingbirds.Here,we studied three additional aspects of its floral biology:sexual phases,nectar dynamics and breeding system,and examined their connection with pollinators’behaviour to explore the presence of adaptations to bee and/or hummingbird pollination.Methods Using a greenhouse population,we applied five pollination treatments to characterize breeding system.To determine sexual phases,we recorded flower opening,anther dehiscence,corolla fall and stigma receptivity.Additionally,we characterized nectar volume and concentration dynamics along the day.Finally,to determine pollinator assemblage and visitation patterns,we performed field observations and recorded pollinators’behaviour.Important Findings Salvia stachydifolia was partially protandrous and self-compatible,but open-pollinated plants attained the highest reproductive success,suggesting that reproduction is mainly dependent on pollinator activity.Bombus opifex bumblebees were the most frequent visitors,but Sappho sparganura hummingbirds dominated visits early in the morning and at dusk.Nectar was typical of bumblebee pollination.We suggest that the bee–hummingbird mixed visitation constitutes an unstable evolutionary situation,making S.stachydifolia an ideal system to understand the ecological circumstances in which pollination shifts occur.
