In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-s...In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-sensor technique becomes an indispensable method to implement real-time quality control. In this article, a new model of multi-inputs multi-outputs （MIMO） soft-sensor, which is constructed based on hybrid modeling technique, is proposed for these interactional variables. Data-driven modeling method and simplified first principle modelingmethod are combined in this model. Data-driven modeling method based on limited memory partial least squares（LM-PLS） al.gorithm is used to build soft-senor models for some secondary variables.then, the simplified first principle model is used to compute three primary variables on line. The proposed model has been used in practicalprocess; the results indicate that the proposed model is precise and efficient, and it is possible to realize on line quality control for compound fertilizer process.展开更多
To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be rob...To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be robust to imperfect CSI.A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed.The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI.Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance.In addition,the effect of spatial correlation on the performance of the proposed algorithm is also simulated.展开更多
基金Supported by the National Natural Science Foundation of China （No.60421002） and the New Century 151 Talent Project of Zhejiang Province.
文摘In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-sensor technique becomes an indispensable method to implement real-time quality control. In this article, a new model of multi-inputs multi-outputs （MIMO） soft-sensor, which is constructed based on hybrid modeling technique, is proposed for these interactional variables. Data-driven modeling method and simplified first principle modelingmethod are combined in this model. Data-driven modeling method based on limited memory partial least squares（LM-PLS） al.gorithm is used to build soft-senor models for some secondary variables.then, the simplified first principle model is used to compute three primary variables on line. The proposed model has been used in practicalprocess; the results indicate that the proposed model is precise and efficient, and it is possible to realize on line quality control for compound fertilizer process.
基金the National Natural Science Foundationof China(No.60572156)
文摘To reduce the performance deterioration induced by imperfect channel state information(CSI) in correlated multiple input multiple output(MIMO) downlink,the linear transmit/receive filters should be optimized to be robust to imperfect CSI.A sub-optimization algorithm based on minimizing sum MSE conditional on available imperfect CSI estimates subject to a per-user power constraint is proposed.The algorithm adapts the existing MMSE algorithm from uncorrelated single-user MIMO system with perfect CSI to correlated MIMO downlink with imperfect CSI.Simulation shows that the suboptimal algorithm can effectively mitigate the performance loss induced by imperfect CSI and has a good convergence performance.In addition,the effect of spatial correlation on the performance of the proposed algorithm is also simulated.
