An Enhanced Particle Swarm Optimization Algorithm

Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.

a real-time path planning approach without the computation of cspace obstacles

An important concept proposed in the early stage of robot path planning field is the shrinking of the robot to a point and meanwhile expanding of the obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision free path for a point robot among the Cspace obstacles. However, the research experiences obtained so far have shown that the calculation of the Cspace obstacles is very hard work when the following situations occur: 1. both the robot and obstacles are not polygons and 2. the robot is allowed to rotate. This situation is even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. Obviously a direct path planning approach without the calculation of the Cspace obstacles is strongly needed. This paper presents such a new real-time robot path planning approach which, to the best of our knowledge, is the first one in the robotic community. The fundamental ideas are the utilization of inequality and optimization technique. Simulation results have been presented to show its merits.

一种基于进化计算的空间飞行器编队重构轨道规划方法

基于进化算法提出了一种两层结构的空间飞行器编队重构的轨道规划算法,高层算法通过优化构型映射来优化编队的总燃耗,实现全局规划并确保飞行器之间保持一定的安全距离以避免相互碰撞;低层规划算法采用Chebyshev多项式逼近控制变量空间,为每颗飞行器规划满足约束条件的最优轨道。该方法充分利用了编队的分布式结构,由各飞行器并行实现各自的轨道规划,能有效解决大型编队的轨道规划问题。仿真结果表明了该方法的有效性。

Boundary conditions at the solid-liquid surface over the multiscale channel size from nanometer to micron

The boundary condition at the solid surface is one of the important problems for the microfluidics. In this paper we study the effects of the channel sizes on the boundary conditions (BC), using the hybrid computation scheme adjoining the molecular dynamics (MD) simulations and the continuum fluid mechanics. We could reproduce the three types of boundary conditions (slip, no-slip and locking) over the multiscale channel sizes. The slip lengths are found to be mainly dependent on the interfacial parameters with the fixed apparent shear rate. The channel size has little effects on the slip lengths if the size is above a critical value within a couple of tens of molecular diameters. We explore the liquid particle distributions nearest the solid walls and found that the slip boundary condition always corresponds to the uniform liquid particle distributions parallel to the solid walls, while the no-slip or locking boundary conditions correspond to the ordered liquid structures close to the solid walls. The slip, no-slip and locking interfacial parameters yield the positive, zero and negative slip lengths respectively. The three types of boundary conditions existing in "microscale" still occur in "macroscale". However, the slip lengths weakly dependent on the channel sizes yield the real shear rates and the slip velocity relative to the solid wall traveling speed approaching those with the no-slip boundary condition when the channel size is larger than thousands of liquid molecular diameters for all of the three types of interfacial parameters, leading to the quasi-no-slip boundary conditions.

1ST PRINCIPLE CALCULATIONS OF QUASI-PARTICLE ENERGIES FOR BAND STRUCTURES OF SI AND GAAS

We have applied the Green function theory in GW approximation to calculate the quasiparticle energies for semiconductors Si and GaAs. Good agreements of the calculated excitation energies and fundamental energy gaps with the experimental band structures were achieved. We obtained the calculated fundamental gaps of Si and GaAs to be 1.22 and 1.42 eV in comparison to the experimental values of 1.17 and 1.52 eV, respectively. Ab initio pseudopotential method has been used to generate basis wavefunctions and charge densities for calculating dielectric matrix elements and electron self-energies.