非收敛的

Based on the analysis of the mechanism of robot manipulators, a trajectory tracking controlling research model is first built up with ADAMS, and its mathematical model is formulated through the study of robot kinematics and dynamics. After the modeling errors are analyzed in practical robotic systems, a conception of centralized error is brought forward according to the theory of weighting functions. In the case of modeling errors' exist, the robotic uncertain model is derived by introducing an auxiliary control variable into inverse dynamic analysis. The control strategy of robust exponential convergence is applied to the robotic uncertain model, the applicable conditions and the applicable controller with this application are presented. The stable control effect under three main model uncertainties (parametric errors, joint disturbs, joint frictions) are systematically studied on the previously built research model. The problems of robust exponential convergence controller which often results in unstable output and so produces a large relative error when the input trajectory is in a small range are resolved by adjusting the control parameters based on the controller's structure.

本文在机械手的机械结构分析基础上，利用ADAMS建立了用于机械手轨线跟踪控制研究的机械手模型；通过对机器人运动学和动力学问题的研究，建立了机械手研究的数学模型；分析了机器人系统中模型误差的主要来源，根据加权函数法分析，提出了模型集中误差的概念；在存有模型误差的情况下，采用逆动力学结构并引入辅助控制量，由机器人误差模型推导了机器人非确定性模型；提出了采用鲁棒指数收敛法对上述机器人非确定性模型进行鲁棒镇定的控制策略，并给出了对机器人进行鲁棒指数收敛控制时系统不确定因素应满足的匹配条件；针对机械手研究模型，深入研究了鲁棒指数收敛控制器对机器人系统中常见的模型参数误差、关节扰动、关节摩擦等不确定因素的镇定控制效果；针对鲁棒指数收敛控制器易产生控制量振荡的问题以及在小范围内系统轨线跟踪的稳态误差过大问题，本文分别提出了基于控制器结构的控制参数调整法和基于轨线跟踪范围大小的控制参数分段切换法。

Furthermore, the first-order optimality condition and its equivalent reformulations for generalized semi-infinite max-min programming with a non-compact set are presented using the lower-Hadamard directional derivative and subdifferential.2. Chapter 3 studies the gradient-type methods for unconstrained optimization problems. Section 1 proposes a new class of three-term memory gradient methods. The global convergence property of the method is established. Furthermore, in order to improve the convergence property of the method, a new class of memory gradient projection methods is presented with the property that the whole sequence of iterates converges to a solution to the problem under the conditions such as pseudo-convexity and continuous differentiability of objective function. In section 2, two new classes of methods, called gradient-type method with perturbations and hybrid projection method with perturbations, are proposed. In these methods, non-monotone line search technique is employed, which makes them easily executed in computer.

第3章研究了无约束优化问题的梯度型算法，第1节提出了一类新的三项记忆梯度算法，讨论了算法的全局收敛性，进一步提出了一类新的具有更好收敛性质的记忆梯度投影算法，并证明了该算法在函数伪凸的情况下具有整体收敛性，第2节在非单调步长搜索下提出了带扰动项的梯度型算法及其混合投影算法，这两类算法的一个重要特征就是步长采用线搜索确定而不象许多文献中那样要求步长趋于零，这样更容易在计算机上实现，在较弱的条件下证明了这些算法的全局收敛性，数值算例表明了算法的有效性。

By the case of skewed cavity flow with 30-degree angle, the convergence performance of SIMPLE/SIMPLEC algorithm was analyzed on unstructured grids and the influence of accepting or rejecting non-orthogonal terms was compared.

利用30°角的斜方腔流动计算成果，分析了非结构同位网格的SIMPLE/SIMPLEC算法的收敛性能；比较了因网格的非正交而引入的非正交项的取舍对该算法收敛性能的影响；并采用显式校正步法对SIMPLEC算法进行了显式校正。

In the fourth chapter,we quoted a normal matrix,and proved a convergence theorem about nonhomogeneous Markov chains.

第四章通过引进一正规矩阵，证明了一个关于非齐次马氏链的收敛定理，是杨卫国等人的一个关于非齐次马氏链Cesaro平均收敛定理的推广。

Combining NA samples the EB estimation with convergence rates is also obtained; Thirdly, for one-parameter exponential distribution family, we give the parameters' EB estimator that is admissible and asymptotically optimal with convergence rates. Finally, Bayesian and hierarchical Bayesian approaches are applied to analyze the reliability performances for series system with cold standby units and the numerical simulation results show that multiple Bayes estimator is superior to Bayes estimator.

其次，针对一类双边截断分布族，在非对称linex损失下构造了经验Bayes决策函数，建立了它的收敛速度，给出了渐近最优的证明；并结合NA样本研究了参数的经验Bayes估计及其收敛速度；接着给出了指数族参数的经验Bayes估计，证明了它是渐近最优的，也是可容许的，同时也获得了该EB估计的收敛速度；最后，运用Bayes与多层Bayes方法研究了具有冷贮备部件串联系统的可靠性指标的估计，并给出了数值模拟结果，结果表明多层Bayes估计优于Bayes估计。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明：在共轭梯度法中引入非负约束和光滑约束改善了迭代的"半收敛"性，非负约束保证了解的非负性，光滑约束抑制了重建解的振荡现象，约束算法的重建精度与无约束算法相比大幅度提高；在约束共轭梯度重建算法中引入预优技术，可以加快算法的收敛速度，提高迭代的稳定性和重建精度；引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性，加快迭代的收敛速度，提高迭代的稳定性和图像重建质量，计算正则参数的TPA算法在闪光照相图像重建中是有效的。

Many methods are used to solve nonlinear problems, their rate of convergence is quick, for example, Newton-moser method, King-werner method, they are attentioned widely because of the quick rate of convergence. While these methods are used to solve singular problems, the rate of convergence is slow, it is discommodious for us to solve practical problems.

有许多方法在求解非奇异问题时，它们的收敛率是很快的，有些甚至能达到二次收敛，例如Newton-Moser法、King-werner法，这是所熟知的，因其收敛速度快，并且简单易用而广受重(来源：AB17C论文dddd网www.abclunwen.com)视。

We study the commmon fixed point of nonexpansive semigroups in Banach space, and obtain some strong connvergence theorems on an iterrative method for a family of nonexpansive mappings in Banach space.

研究了Banach空间上非扩张半群的收敛公共不动点，以及一类有限非扩张映射族的强收敛性。

Inspired by these results, in this paper, we first give the definition of a new mapping ? uniformly Lipschitz asymptotically nonexpansive mapping on a compact subset of a uniform convex Banach space, then construct three-step iterative sequences of uniformly Lipschitz asymptotically nonexpansive mapping in this subset . We proved the convergence of this three-step iterative sequences for uniformly Lipschitz asymptoticallynonexpansive mapping, Further more, we proved this three-step iterative sequences with an error member converge to fixed points.

从中得到启发，在本文我们首先定义了一致凸Banach空间某非空紧子集上的一种新的映射——一致李普希兹渐进非扩张映射，在该紧子集上构造关于一致李普希兹渐进非扩张映射的三步迭代序列以及具误差的三步迭代序列，先来讨论三步迭代序列的收敛性，进而讨论具误差的三步迭代序列的收敛性。

The reconstruction problem is ill-posed, so two optimal criterions, the least module and the smoothness criterion base on Tikhonov regularization technique, are introduced into reconstruction algorithm. Many regularization parameters choice strategies are investigated, and the TPA(Two—Parameter Algorithm) strategy which is based on the Morozov discrepancy principles, is implemented in two regularization reconstruction algorithms.Numerical experiment results show that the nonnegative and smoothness constraint condition can overcome the difficulty of iteration semiconvergent, preconditioned technique can improve convergence rate and reconstruction accuracy, smoothness regularization criterion can meliorate ill-posed problem of reconstruction and enhance iteration stability, and the TPA is an effective strategy of regularization parameters choice.

数值试验表明：在共轭梯度法中引入非负约束和光滑约束改善了迭代的&半收敛&性，非负约束保证了解的非负性，光滑约束抑制了重建解的振荡现象，约束算法的重建精度与无约束算法相比大幅度提高；在约束共轭梯度重建算法中引入预优技术，可以加快算法的收敛速度，提高迭代的稳定性和重建精度；引入光滑准则的正则化技术可以有效改善图像重建问题的不适定性，加快迭代的收敛速度，提高迭代的稳定性和图像重建质量，计算正则参数的TPA算法在闪光照相图像重建中是有效的。

They weren't aggressive, but I yelled and threw a rock in their direction to get them off the trail and away from me, just in case.

他们没有侵略性，但我大喊，并在他们的方向扔石头让他们过的线索，远离我，以防万一。

In slot 2 in your bag put wrapping paper, quantity does not matter in this case.

在你的书包里槽2把包装纸、数量无关紧要。