研究了基于周期反馈MIMO(multiple-input-multiple-output)系统的容量。在给定反馈容量约束(平均每一个块的时间内最多能反馈的比特数)的情况下,当CSI(channel state information)的量化比特数越大时,一方面,CSI的量化误差越小,从而增...研究了基于周期反馈MIMO(multiple-input-multiple-output)系统的容量。在给定反馈容量约束(平均每一个块的时间内最多能反馈的比特数)的情况下,当CSI(channel state information)的量化比特数越大时,一方面,CSI的量化误差越小,从而增大容量;另一方面,反馈周期越大,导致降低容量。因此,对于周期反馈系统的容量而言,存在最优的CSI量化比特数。通过数值计算,给出了最优的CSI量化比特数。计算结果表明:与传统的反馈策略相比,周期反馈策略使得系统容量得到较大提升。展开更多
Subject of the halo-chaos control in beam transport networks （channels） has become a key concerned issue for many important applications of high-current proton beam since 1990＇. In this paper, the magnetic field ad...Subject of the halo-chaos control in beam transport networks （channels） has become a key concerned issue for many important applications of high-current proton beam since 1990＇. In this paper, the magnetic field adaptive control based on the neural network with time-delayed feedback is proposed for suppressing beam halo-chaos in the beam transport network with periodic focusing channels. The envelope radius of high-current proton beam is controlled to reach the matched beam radius by suitably selecting the control structure and parameter of the neural network, adjusting the delayed-time and control coefficient of the neural network.展开更多
By using a fixed point theorem on a cone to investigate the existence of two positive periodic solutions for the following delay difference system with feedback control argument of the form {△x（n）=-b（n）x（n）＋f...By using a fixed point theorem on a cone to investigate the existence of two positive periodic solutions for the following delay difference system with feedback control argument of the form {△x（n）=-b（n）x（n）＋f（n,x（n-τ1（n））,…,x（n-τm（n））,u（n-δ（n）））,△u（n）=-η（n）u（n）＋a（n）x（n-σ（n））,n∈Z.展开更多
Efficiency and accuracy of AFM-based nanomanipulation are still major problems to be solved,due to the nonlinearities and uncertainties,such as drift,creep,hysteresis,etc. The deformation of cantilevers caused by mani...Efficiency and accuracy of AFM-based nanomanipulation are still major problems to be solved,due to the nonlinearities and uncertainties,such as drift,creep,hysteresis,etc. The deformation of cantilevers caused by manipulation force is also one of the most major factors of nonlinearities and uncertainties. It causes difficulties in precise control of the tip position and causes the tip to miss the position of the object. In order to solve this problem,the traditional approach is to use a rigid cantilever. However,this will significantly reduce the sensitivity of force sensing during manipulation,which is essential for achieving an efficient and reliable nanomanipulation. In this paper,a kind of active AFM probe has been used to solve this problem by directly controlling the cantilever’s flexibility or rigidity during manipu-lation. Based on Euller-Bernoulli Model,a kind of controller of the active probe employing Peri-odic-Output-Feedback(POF)law is implemented. The results of simulation and experiments have demonstrated that this theoretical model and POF controller are suitable for precise position control of nanomanipulation.展开更多
文摘研究了基于周期反馈MIMO(multiple-input-multiple-output)系统的容量。在给定反馈容量约束(平均每一个块的时间内最多能反馈的比特数)的情况下,当CSI(channel state information)的量化比特数越大时,一方面,CSI的量化误差越小,从而增大容量;另一方面,反馈周期越大,导致降低容量。因此,对于周期反馈系统的容量而言,存在最优的CSI量化比特数。通过数值计算,给出了最优的CSI量化比特数。计算结果表明:与传统的反馈策略相比,周期反馈策略使得系统容量得到较大提升。
基金The project supported by the Key Projects of National Natural Science Foundation of China under Grant No. 70431002 and National Natural Science Foundation of China under Grants Nos. 70371068 and 10247005
文摘Subject of the halo-chaos control in beam transport networks （channels） has become a key concerned issue for many important applications of high-current proton beam since 1990＇. In this paper, the magnetic field adaptive control based on the neural network with time-delayed feedback is proposed for suppressing beam halo-chaos in the beam transport network with periodic focusing channels. The envelope radius of high-current proton beam is controlled to reach the matched beam radius by suitably selecting the control structure and parameter of the neural network, adjusting the delayed-time and control coefficient of the neural network.
基金Supported by the National Natural Sciences Foundation of China(10361006)Supported by the Natural Sciences Foundation of Yunnan Province(2003A0001M)Supported by the Jiangsu "Qing-lanProject" for Excellent Young Teachers in University(2006)
文摘By using a fixed point theorem on a cone to investigate the existence of two positive periodic solutions for the following delay difference system with feedback control argument of the form {△x（n）=-b（n）x（n）＋f（n,x（n-τ1（n））,…,x（n-τm（n））,u（n-δ（n）））,△u（n）=-η（n）u（n）＋a（n）x（n-σ（n））,n∈Z.
基金the National Natural Science Foundation of China (Grant No.60675050)
文摘Efficiency and accuracy of AFM-based nanomanipulation are still major problems to be solved,due to the nonlinearities and uncertainties,such as drift,creep,hysteresis,etc. The deformation of cantilevers caused by manipulation force is also one of the most major factors of nonlinearities and uncertainties. It causes difficulties in precise control of the tip position and causes the tip to miss the position of the object. In order to solve this problem,the traditional approach is to use a rigid cantilever. However,this will significantly reduce the sensitivity of force sensing during manipulation,which is essential for achieving an efficient and reliable nanomanipulation. In this paper,a kind of active AFM probe has been used to solve this problem by directly controlling the cantilever’s flexibility or rigidity during manipu-lation. Based on Euller-Bernoulli Model,a kind of controller of the active probe employing Peri-odic-Output-Feedback(POF)law is implemented. The results of simulation and experiments have demonstrated that this theoretical model and POF controller are suitable for precise position control of nanomanipulation.
