Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predict...Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predictive control algorithm(SPC). The new method uses model matching error to calculate the variable forgetting factor, and applies it to constructing Hankel data matrix.This makes the data represent the changes of system information better. For eliminating the steady state error, the derivation of the incremental control is made. Simulation results on a rotary kiln show that this control strategy has achieved a good control effect.展开更多
The conflation of geographic datasets is one of the key technologies in the realm of spatial data capture and integration in geographic information system(GIS).Map conflation is a complex process of matching and mergi...The conflation of geographic datasets is one of the key technologies in the realm of spatial data capture and integration in geographic information system(GIS).Map conflation is a complex process of matching and merging spatial data.Due to various reasons such as errors in original data related to map data discrepancies,a great amount of uncertainties exists during the process and this will result in errors in featuring matching,especially point feature.Thus,it is vital to develop the method to detect the errors in feature matching and further the conflation results will not be affected.In this paper,error matching detection and robust estimation adjustment methods are proposed for map conflation.The characteristics of errors in feature matching are first analyzed,then a new approach for map conflation based on the least-squares adjustment is presented,and a robust estimation adjustment method is further proposed to detect and process matching errors.The results of the map conflation test show that the proposed method not only determines the errors in feature matching,but also obtains the optimal merging results in map conflation.展开更多
During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algor...During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algorithm for subimages, a large accumulated error will be made. In this paper, a relaxation algorithm of piecing-error for subimages is presented. It can eliminate the accumulated error in the traditional algorithm and greatly improve the quality of pieced image. Based on an initial pieced image, one can continuously adjust the center of every sub-image and its angle to lessen the error between the adjacent sub-images, so the quality of pieced image can be improved. The presented results indicate that the proposed algorithm can dramatically decrease the error while the quality of ultimate pieced image is still acceptable. The time complexity of this algorithm is O(n lnn).展开更多
Based on a low supply voltage curvature-compensated bandgap reference and central symmetry Q;random walk NMOS current source layout routing method,a 1.2-V 10-bit 100-MSPS CMOS current-steering digital-to-analog conver...Based on a low supply voltage curvature-compensated bandgap reference and central symmetry Q;random walk NMOS current source layout routing method,a 1.2-V 10-bit 100-MSPS CMOS current-steering digital-to-analog converter is implemented in a SMIC 0.13-μm CMOS process.The total consumption is only 10 mW from a single 1.2-V power supply,and the integral and differential nonlinearity are measured to be less than 1 LSB and 0.5 LSB, respectively.When the output signal frequency is 1-5 MHz at 100-MSPS sampling rate,the SFDR is measured to be 70 dB.The die area is about 0.2 mm;.展开更多
文摘Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predictive control algorithm(SPC). The new method uses model matching error to calculate the variable forgetting factor, and applies it to constructing Hankel data matrix.This makes the data represent the changes of system information better. For eliminating the steady state error, the derivation of the incremental control is made. Simulation results on a rotary kiln show that this control strategy has achieved a good control effect.
基金the National Natural Science Foundation of China(Grant Nos.40771174 and 40301043)the Doctoral Program of Higher Education of China(Grant No.20070247046)+1 种基金the Program for ShuGuang Scholarship of Shanghai(Grant No.07SG24)Foundation of Shanghai Ris-ing-Star Program(Grant No.05QMX1456)
文摘The conflation of geographic datasets is one of the key technologies in the realm of spatial data capture and integration in geographic information system(GIS).Map conflation is a complex process of matching and merging spatial data.Due to various reasons such as errors in original data related to map data discrepancies,a great amount of uncertainties exists during the process and this will result in errors in featuring matching,especially point feature.Thus,it is vital to develop the method to detect the errors in feature matching and further the conflation results will not be affected.In this paper,error matching detection and robust estimation adjustment methods are proposed for map conflation.The characteristics of errors in feature matching are first analyzed,then a new approach for map conflation based on the least-squares adjustment is presented,and a robust estimation adjustment method is further proposed to detect and process matching errors.The results of the map conflation test show that the proposed method not only determines the errors in feature matching,but also obtains the optimal merging results in map conflation.
文摘During the process of automatic image recognition or automatic reverse design of IC, people often encounter the problem that some sub-adages must be pieced together into a whole image. In the traditional piecing algorithm for subimages, a large accumulated error will be made. In this paper, a relaxation algorithm of piecing-error for subimages is presented. It can eliminate the accumulated error in the traditional algorithm and greatly improve the quality of pieced image. Based on an initial pieced image, one can continuously adjust the center of every sub-image and its angle to lessen the error between the adjacent sub-images, so the quality of pieced image can be improved. The presented results indicate that the proposed algorithm can dramatically decrease the error while the quality of ultimate pieced image is still acceptable. The time complexity of this algorithm is O(n lnn).
文摘Based on a low supply voltage curvature-compensated bandgap reference and central symmetry Q;random walk NMOS current source layout routing method,a 1.2-V 10-bit 100-MSPS CMOS current-steering digital-to-analog converter is implemented in a SMIC 0.13-μm CMOS process.The total consumption is only 10 mW from a single 1.2-V power supply,and the integral and differential nonlinearity are measured to be less than 1 LSB and 0.5 LSB, respectively.When the output signal frequency is 1-5 MHz at 100-MSPS sampling rate,the SFDR is measured to be 70 dB.The die area is about 0.2 mm;.
