Terminal constrained robust hybrid iterative learning model predictive control for complex time-delayed batch processes

This work mainly addresses terminal constrained robust hybrid iterative learning model predictive control against time delay and uncertainties in a class of complex batch processes with input and output constraints. In this work, an equivalently novel extended two-dimensional switched system is first constructed to represent the process model by introducing state difference, output error and new relaxation variable information. Then, a hybrid predictive updating controller is proposed and an optimal performance index function including terminal constraints is designed. Under the condition that the switching signal meets certain conditions, the solvable problem of model predictive control is realized by Lyapunov stability theory. Meanwhile, the design scheme of controller parameters is also given. In addition, the robust constraint set is adopted to overcome the disadvantage that the traditional asymptotic stability cannot converge to the origin when it involves disturbances, such that the system state converges to the constraint set and meets its expected value. Finally, the effectiveness of the proposed algorithm is verified by controlling the speed and pressure parameters of the injection molding process.     

Multiple decoding for polar-coded chase combining HARQ

The polar-coded hybrid automatic repeat request (HARQ) scheme with chase combining (CC) has very low complexity and is easy to combine with other techniques such as the coded-modulation and space–time coding, etc. However, the CC-HARQ scheme usually suffers from error and throughput performance degradation. A multiple decoding CC-HARQ (MDCC-HARQ) scheme is proposed in this paper by providing extra decoding chances when the joint decoding fails. Specifically, new LLR-sequences are constructed from the received signals, which can be utilized for the extra decoding attempts. Simulation results show that the proposed MDCC-HARQ scheme can achieve better error-performance and higher throughput efficiency, while requires less retransmission when compared with the CC-HARQ scheme.     

AN ITERATIVE METHOD FOR THE DISCRETE PROBLEMS OF A CLASS OF ELLIPTICAL VARIATIONAL INEQUALITIES

ＡＮＩＴＥＲＡＴＩＶＥＭＥＴＨＯＤＦＯＲＴＨＥＤＩＳＣＲＥＴＥＰＲＯＢＬＥＭＳＯＦＡＣＬＡＳＳＯＦＥＬＬＩＰＴＩＣＡＬＶＡＲＩＡＴＩＯＮＡＬＩＮＥＱＵＡＬＩＴＩＥＳＺｈｅｎｇＴｉｅ－ｓｈｅｎｓ（郑铁生）ＬｉＬｉ（李立）ＸｕＱｉｎｇ－ｙｕ（许庆余）（Ｄ...     

确定SOR最佳松弛因子的一个实用算法

SOR迭代方法中的最佳松弛因子的确定 ,是数值代数中的一个理论难题。本文采用优化技术中简便的直接搜索法 ,构造出近似确定最佳松弛因子的数值算法 ,并由此得出一个具有近似确定ωop t功能的自适应 SOR算法 ,数值算例表明 :该算法是实用和快捷的。     

基于捷联惯导的航空重力测量滤波算法

在航空重力测量中通常需要采用卡尔曼滤波来对比力测量误差进行估计。针对航空重力测量只需要进行事后处理的特点，提出了两种新方法来提高比力测量的精度：一是最优卡尔曼滤波平滑算法，该算法的估计值是前向／反向卡尔曼滤波器的估计值的最优组合；二是迭代算法，由于在滤波模型中通常不对重力异常进行建模，而模型误差的存在会降低滤波精度，迭代算法的基本思想是将重力异常估计值代入新的导航解算，以此降低重力异常对滤波估计精度的影响。仿真分析表明所提出的方法能有效提高比力测量的精度，同时表明滤波估计是有偏的，因此还需要采用网格平差等方法来消除系统误差。     

基于电子海图显示信息系统的惯性/地磁组合导航

为实现惯导系统长时间高精度导航,以性能优良的电子海图显示信息系统为开发背景,对地磁匹配辅助惯性导航系统进行了设计和仿真实验。在原有电子海图显示信息系统的基础上开发了数据采集模块、地磁数据库模块、惯导/地磁匹配模块、惯导误差估计模块等功能软件,并对各功能模块进行了深入分析。仿真试验结果证明,基于电子海图显示信息系统的惯性/地磁组合导航达到了校正惯性导航系统,实现高精度导航的目的。     

One approximate solution of the Nekrasov problem

An approximate solution ω = A[ω, μ] of the nonlinear integral Nekrasov equation is obtained by successive replacement of the kernel of the integral operator by a close one. The solution is sought not directly at the bifurcation point μ₁ = 3 of the linearized equation ω = μL[ω] but at the point μ = 1 at which operator A[ω, μ], remaining nonlinear in ω, is linear in μ. __________ Translated from Prikladnaya Mekhanika i Tekhnicheskaya Fizika, Vol. 48, No. 6, pp. 50–56, November–December, 2007.     

A Newton type iterative inverse method for heat-conduction problems

An inverse problem for identification of the coefficient in heat-conduction equation is considered. After reducing the problem to a nonlinear ill-posed operator equation, Newton type iterative methods are considered. The implicit iterative method is applied to the linearized Newton equation, and the key step in the process is that a new reasonable a posteriori stopping rule for the inner iteration is presented. Numerical experiments for the new method as well as for Tikhonov method and Bakushikskii method are given, and these results show the obvious advantages of the new method over the other ones.     

两类五阶解非线性方程组的迭代算法

本文首先根据Runge-Kutta方法的思想,结合Newton迭代法,提出了一类带参数的解非线性方程组F(x)=0的迭代算法,然后基于解非线性方程f(x)=0的King算法,给出第二类解非线性方程组的迭代算法,收敛性分析表明这两类算法都是五阶收敛的.其次给出了本文两类算法的效率指数,以及一些已知算法的效率指数,并且将本文算法的效率指数与其它方法进行详细的比较,通过效率比率R_(i,j)可知本文算法具有较高的计算效率.最后给出了四个数值实例,将本文两类算法与现有的几种算法进行比较,实验结果说明本文算法收敛速度快,迭代次数少,有明显的优势.     

Further study of alternating iterations for rectangular matrices

Theory of matrix splittings is a useful tool in the analysis of iterative methods for solving systems of linear equations. When two splittings are given, it is of interest to compare the spectral radii of the corresponding iteration matrices. This helps to arrive at the conclusion that which splitting should one choose so that one can reach the desired solution of accuracy or the exact solution in a faster way. In the case of many splittings are provided, the comparison of the spectral radii is time-consuming. Such a situation can be overcome by introducing another iteration scheme which converges to the same solution of interest in a much faster way. In this direction, the theory of alternating iterations for real rectangular matrices is recently proposed. In this note, some more results to the theory of alternating iterations are added. A comparison result of two different alternating iteration schemes is then presented which will help us to choose the iteration scheme that will guarantee the faster convergence of the alternating iteration scheme. In addition to these results, a comparison result for proper weak regular splittings is also obtained.