Adaptive broadband beamformer for nonuniform linear array based on second order cone programming

Adaptive broadband beamforraing is a key issue in array applications. The adaptive broadband beamformer with tapped delay line （TDL） structure for nonuniform linear array （NLA） is designed according to the rule of minimizing the beamformer＇s output power while keeping the distortionless response （DR） in the direction of desired signal and keeping the constant beamwidth （CB） with the prescribed sidelobe level over the whole operating band. This kind of beamforming problem can be solved with the interior-point method after being converted to the form of standard second order cone programming （SOCP）. The computer simulations are presented which illustrate the effectiveness of our beamformer.

AN INFEASIBLE-INTERIOR-POINT PREDICTOR-CORRECTOR ALGORITHM FOR THE SECOND-ORDER CONE PROGRAM

A globally convergent infeasible-interior-point predictor-corrector algorithm is presented for the second-order cone programming （SOCP） by using the Alizadeh- Haeberly-Overton （AHO） search direction. This algorithm does not require the feasibility of the initial points and iteration points. Under suitable assumptions, it is shown that the algorithm can find an -approximate solution of an SOCP in at most O（√n ln（ε0/ε）） iterations. The iteration-complexity bound of our algorithm is almost the same as the best known bound of feasible interior point algorithms for the SOCP.

Two new predictor-corrector algorithms for second-order cone programming

Based on the ideas of infeasible interior-point methods and predictor-corrector algorithms, two interior-point predictor-corrector algorithms for the second-order cone programming （SOCP） are presented. The two algorithms use the Newton direction and the Euler direction as the predictor directions, respectively. The corrector directions belong to the category of the Alizadeh-Haeberly-Overton （AHO） directions. These algorithms are suitable to the cases of feasible and infeasible interior iterative points. A simpler neighborhood of the central path for the SOCP is proposed, which is the pivotal difference from other interior-point predictor-corrector algorithms. Under some assumptions, the algorithms possess the global, linear, and quadratic convergence. The complexity bound O（rln（εo/ε）） is obtained, where r denotes the number of the second-order cones in the SOCP problem. The numerical results show that the proposed algorithms are effective.

On Second-Order Duality in Nondifferentiable Continuous Programming

A Mond-Weir type second-order dual continuous programming problem associated with a class of nondifferentiable continuous programming problems is formulated. Under second-order pseudo-invexity and second-order quasi-invexity various duality theorems are established for this pair of dual continuous programming problems. A pair of dual continuous programming problems with natural boundary values is constructed and the proofs of its various duality results are briefly outlined. Further, it is shown that our results can be regarded as dynamic generalizations of corresponding (static) second-order duality theorems for a class of nondifferentiable nonlinear programming problems already studied in the literature.

A VU-decomposition method for a second-order cone programming problem

A vu-decomposition method for solving a second-order cone problem is presented in this paper. It is first transformed into a nonlinear programming problem. Then, the structure of the Clarke subdifferential corresponding to the penalty function and some results of itsvu-decomposition are given. Under a certain condition, a twice continuously differentiable trajectory is computed to produce a second-order expansion of the objective function. A conceptual algorithm for solving this problem with a superlinear convergence rate is given.

Second-Order Duality for Continuous Programming Containing Support Functions

A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order invexity and second-order pseudoinvexity, weak, strong and converse duality theorems are established for this pair of dual problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.

Optimality Conditions and Second-Order Duality for Nondifferentiable Multiobjective Continuous Programming Problems

Fritz John and Karush-Kuhn-Tucker type optimality conditions for a nondifferentiable multiobjective variational problem are derived. As an application of Karush-Kuhn-Tucker type optimality conditions, Mond-weir type second-order nondifferentiable multiobjective dual variational problems is constructed. Various duality results for the pair of Mond-Weir type second-order dual variational problems are proved under second-order pseudoinvexity and second-order quasi-invexity. A pair of Mond-Weir type dual variational problems with natural boundary values is formulated to derive various duality results. Finally, it is pointed out that our results can be considered as dynamic generalizations of their static counterparts existing in the literature.

Linear goal programming approach to obtaining the weights of intuitionistic fuzzy ordered weighted averaging operator

The multiple attribute decision making problems are studied, in which the information about attribute weights is partly known and the attribute values take the form of intuitionistic fuzzy numbers. The operational laws of intuitionistic fuzzy numbers are introduced, and the score function and accuracy function are presented to compare the intuitionistic fuzzy numbers. The intuitionistic fuzzy ordered weighted averaging （IFOWA） operator which is an extension of the well-known ordered weighted averaging （OWA） operator is investigated to aggregate the intuitionistic fuzzy information. In order to determine the weights of intuitionistic fuzzy ordered weighted averaging operator, a linear goal programming procedure is proposed for learning the weights from data. Finally, an example is illustrated to verify the effectiveness and practicability of the developed method.

含SOP的交直流混合配电网日前优化调度

为实现交直流混合配电网的高效运行,提出一种含智能软开关的交直流配电网优化调度方法。在对应用于交直流配电网的智能软开关工作原理进行阐述的基础上,建立含智能软开关的交直流配电网优化调度模型。通过线性化和凸松弛技术,将所建立的非线性优化模型转化为二阶锥规划模型,并且采用改进的50节点算例分析验证模型的有效性。算例结果表明,基于所建模型得到的智能软开关运行策略能够降低配电网运行损耗及改善电压越限的情况,显著提高混合配电网的经济性。

基于改进灰狼优化算法的含光伏配电网动态无功优化

针对光伏并网对配电网造成的电压波动、线损增加,以及光伏和负荷出力的不确定性等问题,本文构建基于二阶锥规划的线性凸优化模型,通过控制有载调压变压器和电容器组动作,以及光伏逆变器和静止无功发生器无功补偿能力约束,对日前日内双时间尺度无功优化模型进行动态分析,在简化求解过程的同时加大找到全局最优解的可能性。提出一种基于混沌学习初始化、非线性收敛因子、最优粒子柯西扰动结合蜘蛛猴算法位置更新方式的改进灰狼优化算法,防止算法陷入局部最优并增强其全局搜索能力。最后,运用改进的灰狼优化算法对含光伏的IEEE 33节点系统进行建模仿真,结果表明该算法具有寻优效率高、收敛速度快的优点,验证了算法的可行性和高效性。

极限下限分析的区域光滑径向点插值法

极限分析的高效数值计算方法在结构设计和安全评定中具有非常重要的作用.为了更加有效地求解极限分析问题,将区域光滑径向点插值法与二阶锥规划相结合,提出了理想弹塑性结构极限下限分析的一种新方法.将问题域离散为简单的三角形背景单元,每个单元进一步划分成若干个光滑域.为了将复杂的域积分转化为简单的边界积分,并且避免计算形函数的导数,采用广义梯度光滑技术对每个光滑域进行应变光滑处理.由于径向点插值法构造的形函数满足Kronecker delta性质,本质边界条件可以直接施加.依据下限定理,在满足以等效积分弱形式表达的自平衡应力场平衡条件的基础上,用二阶锥规划成功构建了极限分析下限法的计算模型,从而可方便地通过基于原始-对偶内点法的数学规划求解器MOSEK直接求解该问题.数值算例结果表明,本文所提方法有效地克服了维数障碍问题,具有较高的计算精度,并且计算结果对网格畸变十分不敏感.

Higher-Order Duality for Minimax Fractional Type Programming Involving Symmetric Matrices

Convexity and generalized convexity play important roles in optimization theory. With the development of programming problem, there has been a growing interest in the higher-order dual problem and a lot of related generalized convexities are given. In this paper, we give the convexity of (F, α ,p ,d ,b , φ )β vector-pseudo- quasi-Type I and formulate a higher-order duality for minimax fractional type programming involving symmetric matrices, and give the weak, strong and strict converse duality theorems under the condition of higher-order (F, α ,p ,d ,b , φ )β vector-pseudoquasi-Type I.

The Second-Order Differential Equation System with the Feedback Controls for Solving Convex Programming

In this paper, we establish the second-order differential equation system with the feedback controls for solving the problem of convex programming. Using Lagrange function and projection operator, the equivalent operator equations for the convex programming problems under the certain conditions are obtained. Then a second-order differential equation system with the feedback controls is constructed on the basis of operator equation. We prove that any accumulation point of the trajectory of the second-order differential equation system with the feedback controls is a solution to the convex programming problem. In the end, two examples using this differential equation system are solved. The numerical results are reported to verify the effectiveness of the second-order differential equation system with the feedback controls for solving the convex programming problem.

含电动汽车的主动配电网多目标分层优化调度

为了协调电动汽车车主和主动配电网2个不同主体之间的利益关系,针对电动汽车接入后主动配电网的优化调度问题,文中提出一种考虑电动汽车充电综合满意度和主动配电网运行效益的多目标分层优化方法。上层模型注重最大化电动汽车车主的充电利益,采用归一化法向约束法求解电动汽车的最优充放电计划,并将其输入下层优化模型。下层模型旨在最大化主动配电网的运行效益,根据电动汽车的充放电计划调整可控分布式电源的输出功率,采用二阶锥松弛转换法和带权极小模理想点法求解该非线性多目标问题。仿真结果表明,所提含电动汽车的主动配电网多目标分层优化方法能够在促使电动汽车充电综合满意度超过0.9的同时,减少有功网损约94.12%、运行成本约30.90%,实现电动汽车车主和主动配电网的双赢。

考虑电压-无功调节的台区互联装置规划方法

伴随分布式能源广泛接入低压配电网,其对配电网运行灵活性和消纳能力的要求不断提高。利用低压柔性互联装置将独立运行的低压配电台区分区互联,避免传统电压调节和无功补偿装置频繁动作。考虑到柔性互联装置造价昂贵,协同传统电压-无功调节装置,文中提出低压柔性互联装置的选址定容规划方法。首先,分析低压柔性互联装置拓扑和运行方式,建立其潮流模型。其次,建立低压柔性互联装置优化配置的双层规划模型,上层规划以年综合费用最小为目标,下层规划考虑电压-无功协调控制时间序列模型,以运行成本和电压偏差最小为目标,基于粒子群优化算法和混合整数二阶锥规划算法交替求解,得出配电系统最优柔性互联方案和最优运行方式。最后,在IEEE 33节点系统上进行实例分析,验证该双层规划算法的有效性。结果表明,所提方法能有效减少柔性互联装置的过度布置,同时减少由分布式能源频繁波动造成的运行成本。将模型凸化并线性化的方法明显提高了求解效率。

基于凸包理论的含风电电力系统负荷恢复方案优化

大停电事故后,合理的负荷恢复策略对加快电力系统恢复、减少停电损失具有重要意义。针对标准交流潮流方程的非凸性导致负荷恢复模型求解效率低的问题,提出了基于凸包理论的含风电电力系统负荷恢复方案优化方法。首先,简要介绍了凸包理论以及非线性函数的凸包构建方法。其次,针对风电出力的不确定性,采用条件风险价值理论处理风电波动带来的风险,进而建立了直角坐标系下基于凸包理论的电力系统负荷恢复二阶锥优化模型,其中,交流潮流方程中的非线性项采用凸包表达。针对无法精确确定凸包参数的问题,提出了基于迭代更新的参数优化方法,减少因凸包引入的松弛误差。所提出的模型为混合整数二阶锥规划模型,可采用商业求解器高效求解。最后,采用IEEE 39节点系统和改进的广东电力系统验证了所提出模型的有效性。

指向高阶思维能力培养的英语师范专业课程建设——以英国文学课程为例

一流本科课程建设背景下,英语师范专业课程建设既要注重专业性和职业性,又要坚持人文性内涵式发展道路。这一学科内涵决定了英语师范专业在课程建设中要兼顾语言学习、思维训练以及人文价值塑造。其中,高阶思维训练则是课程建设的重中之重。高阶思维是学生思辨能力和创新能力的体现,需要在课程学习中不断养成。因此,英语师范生高阶思维能力的培养与课程设置和课程内容的选择密切相关。高校要探索以进阶性、拓展性和跨学科性为原则的课程体系,以批判性和意义生成为导向的课程学习内容,在纵向优化课程设置和横向深化教学内容的基础上,达到培养学生高阶思维能力的目标。英国文学课程更新教学理念、重组教学内容、创新教学方法,为英语师范生高阶思维能力的培养提供案例,也为师范生人才培养方案的制定提供启示。

考虑闭式潮流优化分布的主动配电网供电恢复方法

主动配电网具有灵活的调节能力和快速可靠的运行能力,但柔性多状态开关(SOP)、分布式电源等多种设备的存在,使供电恢复模型复杂,需要研究故障后供电恢复快速决策方法。提出了一种考虑闭式潮流优化分布的主动配电网负荷恢复方案快速决策方法。模拟故障切除后配电网所有联络开关闭式运行状态,基于二阶锥规划求解最优潮流,退出电压低、传输功率小的线路,形成利于供电恢复的配电网含SOP良性网络拓扑。建立基于负荷的功率因数与分级负荷权重的负荷恢复模型,制定负荷供电恢复方案,保证失电负荷严格按优先级获得最大的恢复水平。通过IEEE33、IEEE69节点配电系统进行算例分析,结果表明所提方法能兼顾计算的准确性和快速性。

考虑交通流量和用户行为不确定性的加氢站选址优化模型

加氢站是氢能产业发展的重要基础设施,其布局选址对于氢能在交通领域的推广应用至关重要。为此,提出一种加氢站的选址优化方法。首先,分别以运营商追求捕获交通流量最大化、客户追求获得加氢服务可能性最大化为上、下层目标函数构建了双层规划模型,并引入机会约束规划理论处理了交通流量的不确定性。该模型考虑了客户路径选择的行为特性,能够为交通流量不确定性下的加氢站选址提供重要借鉴。其次,利用KKT条件和确定性等价将所提机会约束双层规划模型转化为了单层的混合整数二阶锥规划问题以实现高效求解。最后,为验证该模型的有效性,以长三角地区交通网络为案例进行了仿真分析。

宽带共形阵基于SRV约束的自适应波束设计

自适应波束形成可以有效抑制非期望信号方向上的干扰信号。针对采用节拍延迟线(Tapped Delay Line,TDL)结构和复数加权系数的宽带共形阵,本文提出一种基于空间响应偏差SRV(Spatial Response Variation)约束的自适应频率不变波束形成器(Frequency Invariant Beamformer,FIB)优化设计方法。该自适应FIB在参考频率上保持预测信号方向无偏响应以及旁瓣级恒定这2个限制条件下,根据对波束形成器输出功率值与平均空间响应偏差值这2项的加权和进行最小化处理的准则进行设计。通过将这种FIB设计问题转化为标准二阶锥规划(Second Order Cone Programming,SOCP)形式后,可以采用内点方法对其进行有效求解。仿真结果验证了本文方法对于宽带共形阵自适应FIB设计的有效性。