摘要：In this paper, we examine the problem of designing power system stabilizer (PSS). A new technique is developed using particle swarm optimization (PSO) combined with linear matrix inequality (LMI). The main feature of PSO, not sticking into a local minimum, is used to eliminate the conservativeness of designing a static output feedback (SOF) stabilizer within an iterative solution of LMIs. The technique is further extended to guarantee robustness against uncertainties wherein power systems operation is changing continuously due to load changes. Numerical simulation ahs illustrated the utility of the developed technique.

摘要：A particle Swarm Optimization (PSO) based design of three-phase induction motors are proposed. The induction motor design is treated as a non-linear and multivariable constrained optimization problem. The annual material cost and the total annual cost of the motor are chosen as two different objective functions. The PSO is used to find a set of optimal design variables of the motor which are then used to predict performance indices and the objective functions. The proposed method is demonstrated for two sample motors, and it is compared with the genetic algorithm (GA) and the conventional design methods. The results show that the PSO-based method effectively solved the induction motor design problems and outperforms the other methods in both the solution quality and computation efficiency.

摘要：A new concept referred to the non-synchronous deformation effect of particle in sheet metal forming is proposed. The results of finite element analysis show that the flow resistance of sheet metal can be effectively reduced and thus the forming property can be greatly improved if the moving and deformation state of the neighboring elements with equal perpendicular distance to the entrance contour of die is non-synchronous. Experiment tests are presented and the results agree well with FEA simulation. In addition, the mechanism of the non-synchronous effect is analyzed in detail.

摘要：选择众多Race Game爱好者支持的主题，是游戏软件制造者创作的活力所在。在《首都高Battle01》的新作中，不仅利用CG再现了真实存在的道路以及行驶的汽车，而且还通过particle表现出汽车在行驶过程中所发生的各种效果。此外，为了使游戏场景更为逼真自然，还进行了多种物理模拟。

摘要：This paper presents a two-level learning method for designing an optimal Radial Basis Function Network (RBFN) using Adaptive Velocity Update Relaxation particle Swarm Optimization algorithm (AVURPSO) and Orthogonal Least Squares algorithm (OLS) called as OLS-AVURPSO method. The novelty is to develop an AVURPSO algorithm to form the hybrid OLS-AVURPSO method for designing an optimal RBFN. The proposed method at the upper level finds the global optimum of the spread factor parameter using AVURPSO while at the lower level automatically constructs the RBFN using OLS algorithm. Simulation results confirm that the RBFN is superior to Multilayered Perceptron Network (MLPN) in terms of network size and computing time. To demonstrate the effectiveness of proposed OLS-AVURPSO in the design of RBFN, the Mackey-Glass Chaotic Time-Series as an example is modeled by both MLPN and RBFN.

摘要：以煤为矿的代表,在对煤的视觉特性进行分析的基础上,基于3dmax particle Flow系统建立了采掘系统中采煤机和提升运输系统中的带式输送机工作过程中煤的模型,采用3dmax自身的渲染器渲染出了该过程的动画,该方法可用于简便真实的展示煤等矿的效果及相关机械的工作原理。

摘要：本文介绍了After Effects的内置插件particle Playground(粒子广场)配合表达式的运用来制作的数字元素扫屏效果两例。

摘要：particle Illusion是一个独立的粒子特效软件,它使用方便,可以快速简单地为图片、动画或视频影片加入粒子特效.

摘要：利用目标高度估计确定目标攻击要害点是精确制导武器信息处理中的一个重要内容。传统方法主要有直接利用几何方法估计和扩展卡尔曼滤波器方法,这两种方法精度都不高。Partic le F ilter是一种新出现的滤波方法,在解决非线性问题中得到了广泛应用。利用Partic le F ilter设计了一种新的目标高度估计算法。该算法通过贝叶斯递推方法,避免了在测量方程非线性很强的时候,扩展卡尔曼滤波器不合理的线性化所带来的误差。仿真结果表明,这种基于Partic le F ilter的目标高度估计算法提高了估计精度和收敛的鲁棒性。

摘要：现有电力系统稳定器(power system stabilizer,PSS)和直流调制多使用本地信号作为控制器反馈输入信号,控制器间的交互作用可能降低甚至破坏系统稳定性。提出了一种基于广域测量信号的PSS与直流调制协调策略,首先通过留数法选择对于振荡模态可观性较强的广域信号作为阻尼控制器备选反馈信号;其次通过相对增益方法选择使PSS和直流调制交互影响最小的备选信号作为最佳反馈信号;而后设计分散控制器,并运用基于混沌和差分进化的混合粒子群优化算法对PSS和直流调制控制器参数进行协调优化。最后,通过EPRI 36节点系统仿真验证了协调策略的正确性和有效性。