Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

Optimal bounded control for maximizing reliability of Duhem hysteretic systems

The optimal bounded control of stochastic-excited systems with Duhem hysteretic components for maximizing system reliability is investigated. The Duhem hysteretic force is transformed to energy-depending damping and stiffness by the energy dissipation balance technique. The controlled system is transformed to the equivalent non- hysteretic system. Stochastic averaging is then implemented to obtain the It5 stochastic equation associated with the total energy of the vibrating system, appropriate for eval- uating system responses. Dynamical programming equations for maximizing system re- liability are formulated by the dynamical programming principle. The optimal bounded control is derived from the maximization condition in the dynamical programming equation. Finally, the conditional reliability function and mean time of first-passage failure of the optimal Duhem systems are numerically solved from the Kolmogorov equations. The proposed procedure is illustrated with a representative example.

OPTIMAL ERROR BOUND IN A SOBOLEV SPACE OF REGULARIZED APPROXIMATION SOLUTIONS FOR A SIDEWAYS PARABOLIC EQUATION

The inverse heat conduction problem （IHCP） is a severely ill-posed problem in the sense that the solution （ if it exists） does not depend continuously on the data. But now the results on inverse heat conduction problem are mainly devoted to the standard inverse heat conduction problem. Some optimal error bounds in a Sobolev space of regularized approximation solutions for a sideways parabolic equation, i. e. , a non-standard inverse heat conduction problem with convection term which appears in some applied subject are given.

NEW BOUNDS ON TIME AND NUMBER OF PROCESSORS FOR MULTIPROCESSOR OPTIMAL SCHEDULES

Two problems for task schedules in a multiprocessor parallel system are discussed in Ans paper (1) given a partially ordered set of tasks represented by the venices of an acyclic directed graph with their corresponding processing bines, derive the lower bound on the Annimum time(LBMT) needed to process the task graph for a given number of processors. (2) Determine the lower bound on minimum number of processors(LBMP) needed to complete those tasks in minimum bine. It is shown that the proposed LBMT is sharper than previously Known values and the comPUtational aspeCts of these bounds are also discussed.

OPTIMAL ERROR BOUNDS FOR THE CUBIC SPLINE INTERPOLATION OF LOWER SMOOTH FUNCTIONS(1)

In this paper,the kernel of the cubic spline interpolation is given.An optimal error bound for the cu- bic spline interpolation of lower smooth functions is obtained.

OPTIMAL ERROR BOUNDS FOR THE CUBIC SPLINE INTERPOLATION OF LOWER SMOOTH FUNCTION(Ⅱ)

Abstract In this paper, by using the explicit expression of the kernel of the cubic spline interpolation, the optimal error bounds for the cubic spline interpolation of lower soomth functions are obtained.

Trust-region based instantaneous optimal semi-active control of long-span spatially extended structures with MRF-04K damper

In the field of civil engineering, magnetorheological fluid （MRF） damper-based semi-active control systems have received considerable attention for use in protecting structures from natural hazards such as strong earthquakes and high winds. In this paper, the MRF damper-based semi-active control system is applied to a long-span spatially extended structure and its feasibility is discussed. Meanwhile, a _trust-region method based instantaneous optimal semi-active control algorithm （TIOC） is proposed to improve the performance of the semi-active control system in a multiple damper situation. The proposed TIOC describes the control process as a bounded constraint optimization problem, in which an optimal semi- active control force vector is solved by the trust-region method in every control step to minimize the structural responses. A numerical example of a railway station roof structure installed with MRF-04K dampers is presented. First, a modified Bouc- Wen model is utilized to describe the behavior of the selected MRF-04K damper. Then, two semi-active control systems, including the well-known clipped-optimal controller and the proposed TIOC controller, are considered. Based on the characteristics of the long-span spatially extended structure, the performance of the control system is evaluated under uniform earthquake excitation and travelling-wave excitation with different apparent velocities. The simulation results indicate that the MR fluid damper-based semi-active control systems have the potential to mitigate the responses of full-scale long-span spatially extended structures under earthquake hazards. The superiority of the proposed TIOC controller is demonstrated by comparing its control effectiveness with the clipped-optimal controller for several different cases.

Optimal observation configuration of UAVs based on angle and range measurements and cooperative target tracking in three-dimensional space

This article investigates the optimal observation configuration of unmanned aerial vehicles(UAVs) based on angle and range measurements, and generalizes predecessors' researches in two dimensions into three dimensions. The relative geometry of the UAVs-target will significantly affect the state estimation performance of the target, the cost function based on the Fisher information matrix(FIM) is used to derive the FIM determinant of UAVs' observation in three-dimensional space, and the optimal observation geometric configuration that maximizes the determinant of the FIM is obtained. It is shown that the optimal observation configuration of the UAVs-target is usually not unique, and the optimal observation configuration is proved for two UAVs and three UAVs in three-dimension. The long-range over-the-horizon target tracking is simulated and analyzed based on the analysis of optimal observation configuration for two UAVs. The simulation results show that the theoretical analysis and control algorithm can effectively improve the positioning accuracy of the target. It can provide a helpful reference for the design of over-the-horizon target localization based on UAVs.

On Construction of Optimal A^2-Codes

Two authentication codes with arbitration (A 2 codes) are constructed from finite affine spaces to illustrate for the first time that the information theoretic lower bounds for A 2 codes can be strictly tighter than the combinatorial ones. The codes also illustrate that the conditional combinatorial lower bounds on numbers of encodingdecoding rules are not genuine ones. As an analogue of 3 dimensional case, an A 2 code from 4 dimensional finite projective spaces is constructed, which meets both the information theoretic and combinatorial lower bounds.

基于D-optimality准则的多输入多输出雷达阵列设计

为了最小化参数估计的均方误差,提出了基于D-optimality准则(DOBC)的多输入多输出雷达天线几何设计方法。严格推导了天线几何在DOBC准则下需要满足的约束条件;进行了敏感性分析,DOBC准则下的天线几何只与目标方位角之差有关,而与具体的方位角值无关;并推导了远场条件下参数估计的克拉美罗界(CRLB),DOBC准则可以看成一种修正的CRLB,其为最大似然估计算法提供了更严格的下界约束。仿真结果表明,与最小冗余阵列、均匀阵列相比,DOBC准则下的天线几何具有更优越的参数估计性能,且其不受阵列孔径的约束,可以通过扩大孔径,进一步提高分辨力。但随着孔径的提高,方向图的伪峰值会升高,在低信噪比条件下,会造成很大的参数估计误差,因此需要根据实际应用需求,选择合适的孔径大小。

A SPARSE SUBSPACE TRUNCATED NEWTON METHOD FOR LARGE-SCALE BOUND CONSTRAINED NONLINEAR OPTIMIZATION

In this paper we report a sparse truncated Newton algorithm for handling large-scale simple bound nonlinear constrained minimixation problem. The truncated Newton method is used to update the variables with indices outside of the active set, while the projected gradient method is used to update the active variables. At each iterative level, the search direction consists of three parts, one of which is a subspace truncated Newton direction, the other two are subspace gradient and modified gradient directions. The subspace truncated Newton direction is obtained by solving a sparse system of linear equations. The global convergence and quadratic convergence rate of the algorithm are proved and some numerical tests are given.

GLOBAL CONVERGENCE OF TRUST REGION ALGORITHM FOR EQUALITY AND BOUND CONSTRAINED NONLINEAR OPTIMIZATION

This paper presents a trust region two phase model algorithm for solving the equality and bound constrained nonlinear optimization problem. A concept of substationary point is given. Under suitable assumptions,the global convergence of this algorithm is proved without assuming the linear independence of the gradient of active constraints. A numerical example is also presented.

A branch-and-bound algorithm for discrete multi-factor portfolio optimization model

In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial optimization. This discrete portfolio model is of integer quadratic programming problems. The separable structure of the model is investigated by using Lagrangian relaxation and dual search. Computational results show that the algorithm is capable of solving real-world portfolio problems with data from US stock market and randomly generated test problems with up to 120 securities.

Newton, Halley, Pell and the Optimal Iterative High-Order Rational Approximation of √<span style='margin-left:-2px;margin-right:2px;border-top:1px solid black'>N</span>

In this paper we examine single-step iterative methods for the solution of the nonlinear algebraic equation f (x) = x2 - N = 0 , for some integer N, generating rational approximations p/q that are optimal in the sense of Pell’s equation p2 - Nq2 = k for some integer k, converging either alternatingly or oppositely.

The Harvesting Optimal Problem of Richards Model

In this paper, the exploitation of single population modelled by Richards model is studied. By choosing the maximum annual-sustainable yield as management objective, we investigate the optimal harvesting policies for autonomous and periodic exploited Richards model. Further, when the functions in the exploited Richards model are stably bounded functions, we study the ultimately optimal harvesting policy and obtain the corresponding average limiting maximum sustainable yield.

The Optimal Matching Parameter of Half Discrete Hilbert Type Multiple Integral Inequalities with Non-Homogeneous Kernels and Applications

By using the weight function method,the matching parameters of the half discrete Hilbert type multiple integral inequality with a non-homogeneous kernel K(n,||x||ρ,m)=G(nλ1||x||ρmλ,2)are discussed,some equivalent conditions of the optimal matching parameter are established,and the expression of the optimal constant factor is obtained.Finally,their applications in operator theory are considered.

A Bound Heuristic Technique for Solving DRAMA Spares Optimizations

This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory system. The computation of its system spares availability is much complicated. The objective function and constraint functions of DRAMA model could be written as the separable forms. A new bound heuristic algorithm has been presented by improving the bound heuristic algorithm for solving the reliability redundancy optimization problem (BHA in short). With the results, the proposed algorithm has been found to be more economical and effective than BHA to obtain the solutions of large DRAMA model. The new algorithm could be used to solve reliability redundancy optimization problems with the separable forms.

On invariant ellipsoids for discrete-time systems by saturated optimal controls

Analytical approximation of the maximal invariant ellipsoid for discrete-time linear systems with saturated optimal control is established, which is less conservative than existing computationally un-intensive results. Simultaneously, necessary and sufficient conditions for such approximation being equal to the real maximal invariant ellipsoid is presented. All results are given analytically and can easily be implemented in practice. An illustrative example is given to show the effectiveness of the proposed approach.

MaaS模式下城市路网异质出行者逐日流量分配模型

为研究出行即服务(MaaS)模式下的城市路网异质用户逐日路径选择行为和路网流量分配演变规律,将出行者分为选择MaaS服务的平台用户和自主决策的自由用户。建立了两类用户总量的逐日调整模型、自由用户的逐日选择模型及平台用户的系统最优分配模型,并利用不动点理论分析了模型稳定性。算例结果表明:若流量转移函数连续,则模型存在不动点,路径流量能收敛到稳定状态;异质用户路网能降低总出行时间,但达到稳态所需时间更长;高比例的平台用户路网总出行时间更小,更有利于路网优化;提升路网出行服务水平可以使路网稳定在最优态。

考虑材料参数不确定性结构动力学稳健性拓扑优化设计

本文在考虑材料参数不确定性的条件下,对连续体结构动力学稳健性拓扑优化设计进行研究。在使结构的第一阶固有频率最大化的同时,显著减小其对材料性能不确定性的影响。基于非概率凸集模型,将材料参数的不确定性用有界区间变量表示;建立了能够抑制频率改变的结构动力学拓扑优化模型,用单层优化策略求解稳健性优化设计问题。通过对材料参数的导数分析,获得了在材料性能不确定情形下结构第一阶固有频率的二阶泰勒展开式,并推导出了频率对拓扑变量的一阶灵敏度显性表达式。基于变密度法,开展了结构动力学稳健性拓扑优化设计,并与确定性优化结果进行对比,验证了用本文方法获得的结构第一阶固有频率稳健性更高,受材料参数不确定性扰动影响更小,展示了考虑材料参数不确定性的重要性。