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约束优化

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The apriori and aposteriori H〓-optimal filtering question can be solved directly. L〓 Apriori and aposteriori filtering with an H〓 error bound can be solved by semidefinite programming. Robust H〓 apriori filtering and robust apriori L〓 filtering in discrete-time system are subject to a nonconvex constraint.

对这些滤波问题解法的改进同连续系统下的情况基本类似,对确定性系统的H〓验前滤波和验后滤波,本文解法可直接得出最优滤波问题的解;对H〓约束下的L〓验前滤波及验后滤波,其解可归结为一凸优化问题;但不确定性系统H〓验前滤波和鲁棒L〓验前滤波的LMI解法中有了非凸约束,因此要用迭代法求解。

Moreover, it makes the coefficient matrix of centralized IPM's linear correction equation a block diagonal bordered matrix, which can be decomposed into the constraints equation on internal variables of independent sub-areas and coupled constraints equation. During each IPM iteration, internal variables and coupled variables are solved distributedly; thus distributed algorithm of multi-area ORPF is implemented.

在此基础上,论文将该线性方程分解为相互独立的子区域内部约束方程和复制节点的耦合约束方程,在每次内点法迭代中分布分块求解内部变量和耦合变量,从而实现多区域无功优化的分布式计算。

On the basis of general Krawczyk-Hansen Operator, the interval iteration of the constrained functions are established; the interval extension of maximum entropy function is discussed; convergence is proved; region deletion rules are supplied and the algorithm of interval maximum entropy has been set up.

利用极大熵函数和罚函数将问题转化为无约束可微优化问题,借助广义Krawczyk-Hansen算子建立了约束函数的区间迭代;讨论了极大熵函数和罚函数的区间扩张,证明了收敛性等性质,给出了无解区域删除原则,建立了区间极大熵算法。

A study of the problem's model was made. To this problem, the models of single data transmission task and satellite data transmission task were constructed firstly. Based on these models, the model of this problem was constructed, and the object function and main constraints were analyzed especially. For solving the problem, a heuristic scheduling algorithm named double complex priority algorithm was presented and validated by an example lastly.

首先建立了单数传任务模型及卫星数传任务模型;然后在此基础上建立了问题的约束满足优化模型,重点分析了问题的目标函数及主要约束条件;为了解决该问题,最后提出了一个基于双综合优先度的启发式调度算法,并通过实例验证了算法的有效性。

It transforms the primal problem into an ordinary optimization problem with an explicit dual function and simple constraints, with smaller size than primal constraints. It is convenient for engineering application.

该方法不仅给出了原问题显式形式的对偶函数,而且对偶变量的数目仅等于原问题部分约束的个数,原来的线性0-1规划问题被转化为只有简单约束的普通优化问题,极大地方便了工程应用。

Secondly, make amendments to the initial feasible direction in order to adapt it to all the inequations of the optimization model.

具体做法是:首先对非线性优化模型中所有等式约束条件实施拟牛顿迭代法,求得一个可行方向,然后对这个可行方向进行修正,使之满足线性和非线性的不等式约束条件,最后收敛于问题的最优解。

Moreover, A very general optimization problems with a complementarity problem constraint, a inequality and a equality constraints, and an abstract constraint are studied.

最后,我们应用Mordukhovich广义导数方法,在较弱的约束规范性条件—静态条件下,研究当f,g,h,G,H为非光滑函数时,互补约束的优化问题的最优必要性条件。

Screw parameters in VGCN specified by tolerances in TN are expressed as inequation, which is inequation constraint in optimization of tolerance values.

研究了公差网络中的各公差对相应的旋量参数的约束不等式表示,从而构成了公差大小优化的不等式约束。

On the modeling and optimization platform, models of two types of working mechanisms—reverse-turning six-bar linkage has been generated.

在机械设计研究所自行开发的建模平台上,对反转六连杆机构建立了参数优化模型,确定了变量系统,目标和约束系统,用优化软件进行了优化设计。

The boundary of analytical model and statistical model is clearly divided in this performance model, and evaluation accuracy is improved. Secondly, based on embedded SRAM performance hybrid model, this article adopts bionics algorithm-ant algorithm to optimize hierarchical embedded SRAM structure. This method which adjusts memory system structure improves memory system performance. Finally, considering the factors such as memory cell area, power, delay and reliability, this article establishes static 6-T memory cell area, power, delay and static noise margin equations, analyzes 6-T memory cell device dimension constraints under "read upset" and "write upset", then proposes a method to enhance embedded SRAM performance by optimizing 6-T memory cell size. In order to realize embedded SRAM design and verify proposed optimization methods, this article takes the Garfield202 system chip as the platform, which embeds A720T processor and 20KB Scratch-Pad memory.

首先针对嵌入式SRAM结构,采用多元线性回归方法分析SRAM宏单元性能指标,采用解析方法分析控制电路延时,结合以上这两种方法建立嵌入式SRAM性能混合模型,该模型清晰划分两种建模方法的各自适用范围,提高了模型精度;其次以该混合模型为基础建立存储体性能目标函数,采用仿生优化算法—蚂蚁算法优化嵌入式SRAM结构,使之达到最优设计;最后综合考虑面积、功耗、速度以及可靠性等因素,建立静态6-T存储单元面积、功耗、延时以及静态噪声容限方程,分析了&读破坏&和&写破坏&的晶体管尺寸约束,优化了6-T存储单元尺寸,提高了嵌入式SRAM性能。

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