Anti-interference beam pattern design based on second-order cone programming optimization

When signal-to-interference ratio is low, the energy of strong interference leaked from the side lobe of beam pattern will infect the detection of weak target. Therefore, the beam pattern needs to be optimized. The existing Dolph-Chebyshev weighting method can get the lowest side lobe level under given main lobe width, but for the other non-uniform circular array and nonlinear array, the low side lobe pattern needs to be designed specially. The second order cone programming optimization （SOCP） algorithm proposed in the paper transforms the optimization of the beam pattern into a standard convex optimization problem. Thus there is a paradigm to follow for any array formation, which not only achieves the purpose of Dolph-Chebyshev weighting, but also solves the problem of the increased side lobe when the signal is at end fire direction The simulation proves that the SOCP algorithm can detect the weak target better than the conventional beam forming.

Improved design of reconfigurable frequency response masking filters based on second-order cone programming

In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that separately design the proposed method takes all the desired designing modes into consideration when designing all the subfilters. First an initial solution is obtained by separately designing the subfilters and then the initial solution is updated by iteratively solving a SOCP problem. The proposed method is evaluated on a design example and simulation results demonstrate that jointly designing all the subfilters can obtain significantly lower minimax approximation errors compared to the conventional design method.

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.

Robust Blind Separation for MIMO Systems against Channel Mismatch Using Second-Order Cone Programming

To improve the deteriorated capacity gain and source recovery performance due to channel mismatch problem,this paper reports a research about blind separation method against channel mismatch in multiple-input multiple-output(MIMO) systems.The channel mismatch problem can be described as a channel with bounded fluctuant errors due to channel distortion or channel estimation errors.The problem of blind signal separation/extraction with channel mismatch is formulated as a cost function of blind source separation(BSS) subject to the second-order cone constraint,which can be called as second-order cone programing optimization problem.Then the resulting cost function is solved by approximate negentropy maximization using quasi-Newton iterative methods for blind separation/extraction source signals.Theoretical analysis demonstrates that the proposed algorithm has low computational complexity and improved performance advantages.Simulation results verify that the capacity gain and bit error rate(BER) performance of the proposed blind separation method is superior to those of the existing methods in MIMO systems with channel mismatch problem.

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.

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.

SMOOTHING NEWTON ALGORITHM FOR THE CIRCULAR CONE PROGRAMMING WITH A NONMONOTONE LINE SEARCH

In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space with the circular cone. Based on the relationship between the circular cone and the second-order cone(SOC), we reformulate the CCP problem as the second-order cone problem(SOCP). By extending the nonmonotone line search for unconstrained optimization to the CCP, a nonmonotone smoothing Newton method is proposed for solving the CCP. Under suitable assumptions, the proposed algorithm is shown to be globally and locally quadratically convergent. Some preliminary numerical results indicate the effectiveness of the proposed algorithm for solving the CCP.

Spacecraft Attitude Control with Saturation and Attitude Forbidden Constraints via Second⁃Order Cone Programming

This paper investigates the optimal control problem of spacecraft reorientation subject to attitude forbidden constraints,angular velocity saturation and actuator saturation simultaneously.A second-order cone programming(SOCP)technology is developed to solve the strong nonlinear and non-convex control problem in real time.Specifically,the nonlinear attitude kinematic and dynamic are transformed and relaxed to a standard affine system,and linearization and L1 penalty technique are adopted to convexify non-convex inequality constraints.With the proposed quadratic performance index of angular velocity,the optimal control solution is obtained with high accuracy using the successive SOCP algorithm.Finally,the effectiveness of the algorithm is validated by numerical simulation.

Day-ahead Optimization Schedule for Gas-electric Integrated Energy System Based on Second-order Cone Programming

This paper proposes an optimal day-ahead opti-mization schedule for gas-electric integrated energy system(IES)considering the bi-directional energy flow.The hourly topology of electric power system(EPS),natural gas system(NGS),energy hubs(EH)integrated power to gas(P2G)unit,are modeled to minimize the day-ahead operation cost of IES.Then,a second-order cone programming(SOCP)method is utilized to solve the optimization problem,which is actually a mixed integer nonconvex and nonlinear programming issue.Besides,cutting planes are added to ensure the exactness of the global optimal solution.Finally,simulation results demonstrate that the proposed optimization schedule can provide a safe,effective and economical day-ahead scheduling scheme for gas-electric IES.

Optimal design and verification of temporal and spatial filters using second-order cone programming approach

Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming （SOCP） and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.

Nonsingularity in second-order cone programming via the smoothing metric projector

Based on the differential properties of the smoothing metric projector onto the second-order cone,we prove that,for a locally optimal solution to a nonlinear second-order cone programming problem,the nonsingularity of the Clarke's generalized Jacobian of the smoothing Karush-Kuhn-Tucker system,constructed by the smoothing metric projector,is equivalent to the strong second-order sufficient condition and constraint nondegeneracy,which is in turn equivalent to the strong regularity of the Karush-Kuhn-Tucker point.Moreover,this nonsingularity property guarantees the quadratic convergence of the corresponding smoothing Newton method for solving a Karush-Kuhn-Tucker point.Interestingly,the analysis does not need the strict complementarity condition.

Exact Computable Representation of Some Second-Order Cone Constrained Quadratic Programming Problems

Solving the quadratically constrained quadratic programming(QCQP)problem is in general NP-hard.Only a few subclasses of the QCQP problem are known to be polynomial-time solvable.Recently,the QCQP problem with a nonconvex quadratic objective function over one ball and two parallel linear constraints is proven to have an exact computable representation,which reformulates the original problem as a linear semidefinite program with additional linear and second-order cone constraints.In this paper,we provide exact computable representations for some more subclasses of the QCQP problem,in particular,the subclass with one secondorder cone constraint and two special linear constraints.

基于SOCP的采样矩阵求逆算法分析

为克服自适应波束形成技术中采样矩阵求逆(SMI)算法存在计算繁琐、运算量庞大等缺点,提出一种基于二阶锥规划(SOCP)算法的采样矩阵求逆改进算法,即针对SMI算法中数据块生成权向量的最小二乘模型,将其转化为二阶锥规划(SOCP)形式,然后使用SOCP优化方法能够快速准确地求出最优解.实际仿真结果表明:基于SOCP的SMI改进算法(SOCP-SMI)具有计算精确高、运算量小,且对波束特性的改善效果明显.

Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming

In this paper,we accomplish the unified convergence analysis of a second-order method of multipliers(i.e.,a second-order augmented Lagrangian method)for solving the conventional nonlinear conic optimization problems.Specifically,the algorithm that we investigate incorporates a specially designed nonsmooth(generalized)Newton step to furnish a second-order update rule for the multipliers.We first show in a unified fashion that under a few abstract assumptions,the proposed method is locally convergent and possesses a(nonasymptotic)superlinear convergence rate,even though the penalty parameter is fixed and/or the strict complementarity fails.Subsequently,we demonstrate that for the three typical scenarios,i.e.,the classic nonlinear programming,the nonlinear second-order cone programming and the nonlinear semidefinite programming,these abstract assumptions are nothing but exactly the implications of the iconic sufficient conditions that are assumed for establishing the Q-linear convergence rates of the method of multipliers without assuming the strict complementarity.

A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

大规模阵列Kronecker稳健波束形成器

针对大规模阵列对样本需求量大、计算复杂度高的问题,提出一种应用于大规模阵列的Kronecker自适应稳健波束形成器。首先,将期望信号导向矢量分解成两个导向矢量的Kronecker乘积,将原始导向矢量的失配问题转化为两个低维导向矢量的失配问题;然后,基于最坏情况性能最优原理建立双二次代价函数,并利用双迭代算法求解该代价函数,每次迭代过程只需求解两个低维的二阶锥规划问题。理论分析和仿真实验结果表明,与传统全维稳健算法相比,所提方法能够有效降低计算复杂度和样本需求量,与现有的降维稳健算法相比,由于具有更多自由度,所提方法具有更高的输出信干噪比。

考虑间断速度场的光滑有限元极限分析上限法

基于应变光滑技术的有限元极限分析方法,为岩土工程稳定性分析提供了一种有效和高精度的数值分析途径。通过改进基于节点光滑域的方法,使其可以考虑间断的运动许可速度场,提出一种新型节点光滑有限元极限分析上限法。在土与结构接触面处引入间断速度场,以间断面处节点速度差表征间断速度场的大小,进而基于间断节点重新构造节点光滑域。在Mohr-Coulomb屈服准则和关联流动法则的基础上,分别计算间断面和光滑域内的内能耗散,并将屈服准则和流动法则的约束条件转化为一系列的二阶锥约束方程,最终将考虑间断速度场的节点光滑有限元上限法转化为标准的二阶锥规划模型。此模型可以采用高效的原对偶内点算法进行求解。通过岩土工程中经典问题的数值分析,验证了新方法的可靠性,并通过数值分析发现,结构与土体接触的强度性质对结构的失稳模式和极限承载力具有明显的影响。

Quadratic Optimization over a Second-Order Cone with Linear Equality Constraints

This paper studies the nonhomogeneous quadratic programming problem over a second-order cone with linear equality constraints.When the feasible region is bounded,we show that an optimal solution of the problem can be found in polynomial time.When the feasible region is unbounded,a semidefinite programming(SDP)reformulation is constructed to find the optimal objective value of the original problem in polynomial time.In addition,we provide two sufficient conditions,under which,if the optimal objective value is finite,we show the optimal solution of SDP reformulation can be decomposed into the original space to generate an optimal solution of the original problem in polynomial time.Otherwise,a recession direction can be identified in polynomial time.Numerical examples are included to illustrate the effectiveness of the proposed approach.

基于混合整数二阶锥规划的主动配电网有功–无功协调多时段优化运行

通过日前多时段优化,可以为主动配电网中的分布式电源、无功补偿装置和储能装置安排合理高效的生产计划,以达到调节电压水平、提高能源资源利用率、节能降损的目的。首先建立基于三相Distflow潮流的辐射状配电网有功–无功协调动态优化模型。该模型考虑分布式电源出力、储能装置充放电功率、电容器阻投切等连续和离散决策变量,是一个典型的混合整数非凸非线性规划。该类模型缺乏严格高效的求解方法。为此,采用二阶锥松弛技术将其中的三相潮流方程进行凸化松弛,使得优化问题转化为可有效求解的混合整数二阶锥规划模型。最后,采用扩展的IEEE 33节点三相测试系统仿真计算,利用MOSEK等算法包求得电网中各设备动作时刻和投运容量,验证了所提方法寻优稳定、松弛精确、计算高效等特性。

基于鲁棒均值–方差优化的发电自调度算法及鲁棒代价分析

解除管制电力市场背景下,发电厂商作为价格的接受者,需向电力交易中心提供发电交易策略来最大化自身的收益,从而形成发电自调度的优化模型。然而,当考虑电价不确定性时,发电商一方面希望最大化收益,另一方面需要最小化不确定性带来的风险。为此,该文建立了一种鲁棒均值方差优化模型,以收益最大化和风险最小化为多目标,进而获得多目标优化的Pareto前沿。通过等价转化发现,鲁棒均值方差模型与非鲁棒均值方差模型具有相同的数学形式,均为一个二阶锥优化。进一步分析了鲁棒模型对收益、风险以及Pareto前沿的代价。最后采用30节点系统对鲁棒均值方差优化的发电厂自调度模型以及鲁棒代价进行详细的分析和对比,结果证明提出方法和分析的正确性。