基于动态布谷鸟搜索算法的PID控制器参数优化

针对传统PID控制器参数优化费时且不能保证获得最佳性能,提出一种基于动态布谷鸟搜索算法的PID控制器参数优化方法。布谷鸟搜索算法(CS)具有参数少、搜索能力强等特点,但是标准布谷鸟搜索算法参数采用固定值,极大地影响了算法的性能,因此提出了动态布谷鸟搜索算法(DCS),DCS算法采用动态参数,算法性能明显改善。仿真试验结果表明基于动态布谷鸟搜索算法的PID控制器具有较好的控制性能指标。     

基于远程控制的六足搜救机器人系统的设计

针对灾后现场环境的危险性与复杂性,设计了一套搜救机器人系统。在基于仿生学的基础上设计机器人六足式移动平台,以Atmega128型单片机为控制核心,通过步态与动作控制,使之具有强大的越障能力和机体灵活性。整个搜救系统分为机器人系统和控制中心系统两大部分。机器人系统配有完备的传感器模块以及高清摄像头,通过无线传输技术,可在0-1000米范围内实现向控制中心系统上位机的数据与图像传输,并接受上位机控制指令,控制中心根据采集到的信息,可以有效指挥现场搜救人员,大大提高了搜救速度与效率。     

Efficiency of random search procedures along the silicon cluster series: Si(n) (n=5-10, 15, and 20)

The efficiency of the simplest isomeric search procedure consisting in random generation of sets of atomic coordinates followed by density functional theory geometry optimization is tested on the silicon cluster series (Si(5-10, 15, 20)). Criteria such as yield, isomer distributions and recurrences are used to clearly establish the performance of the approach with respect to increasing cluster size. The elimination of unphysical candidate structures and the use of distinct box shapes and theoretical levels are also investigated. For the smaller Si(n) (n=5-10) clusters, the generation of random coordinates within a spherical box is found to offer a reasonable alternative to more complex algorithms by allowing straightforward identification of every known low-lying local minima. The simple stochastic search of larger clusters (i.e. Si(15) and Si(20)) is however complicated by the exponentially increasing number of both low- and high-lying minima leading to rather arbitrary and non-comprehensive results.     

Conformational searching using a population-based incremental learning algorithm

A new population-based incremental learning algorithm for conformational searching of molecules is presented. This algorithm is particularly effective at determining, by relatively small number of energy minimizations, global energy minima of large flexible molecules. The algorithm is also able to find a large set of low energy conformations of more rigid small molecules. The performance of the algorithm is relation to other algorithm is examined via the test molecules: C(18) H(38) , C(39)H(80) , cycloheptadecane and a set of five drug-like molecules.     

Protein structure predictions by parallel simulated annealing molecular dynamics using genetic crossover

We propose a conformational search method to find a global minimum energy structure for protein systems. The simulated annealing is a powerful method for local conformational search. On the other hand, the genetic crossover can search the global conformational space. Our method incorporates these attractive features of the simulated annealing and genetic crossover. In the previous works, we have been using the Monte Carlo algorithm for simulated annealing. In the present work, we use the molecular dynamics algorithm instead. To examine the effectiveness of our method, we compared our results with those of the normal simulated annealing molecular dynamics simulations by using an α-helical miniprotein. We used genetic two-point crossover here. The conformations, which have lower energy than those obtained from the conventional simulated annealing, were obtained.     

A versatile method for systematic conformational searches: application to CheY

A novel molecular structure prediction method, the Z Method, is described. It provides a versatile platform for the development and use of systematic, grid‐based conformational search protocols, in which statistical information (i.e., rotamers) can also be included. The Z Method generates trial structures by applying many changes of the same type to a single starting structure, thereby sampling the conformation space in an unbiased way. The method, implemented in the CHARMM program as the Z Module, is applied here to an illustrative model problem in which rigid, systematic searches are performed in a 36‐dimensional conformational space that describes the relative positions of the 10 secondary structural elements of the protein CheY. A polar hydrogen representation with an implicit solvation term (EEF1) is used to evaluate successively larger fragments of the protein generated in a hierarchical build‐up procedure. After a final refinement stage, and a total computational time of about two‐and‐a‐half CPU days on AMD Opteron processors, the prediction is within 1.56 Å of the native structure. The errors in the predicted backbone dihedral angles are found to approximately cancel. Monte Carlo and simulated annealing trials on the same or smaller versions of the problem, using the same atomic model and energy terms, are shown to result in less accurate predictions. Although the problem solved here is a limited one, the findings illustrate the utility of systematic searches with atom‐based models for macromolecular structure prediction and the importance of unbiased sampling in structure prediction methods. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Multi-residue analysis of pesticides in tea by online SEC-GC/MS

A multi-residue method for the analysis of pesticides in tea was developed by online size exclusion chromatography (SEC)-GC/MS with full scan mode. The sample was fortified with chlorpyrifos-d(10) isotope internal standard and extracted by acetonitrile. After purification by primary secondary amine sorbent and solvent exchange by SEC mobile phase, the sample was detected by online SEC-GC/MS. The purification result of the online system was evaluated by comparing the correlation between Chinese cabbage and tea matrix. The factors for method optimization included sample preparation, matrix effects and the instrument parameters of each online component. Scatter plot was introduced in this study to directly illustrate the results of the condition optimization and matrix effects in the online system. For most of the pesticides, the average recoveries ranged from 70 to 130% and the RSD were below 15%. The feasibility of the application of full scan mode in multi-residue determination of trace amounts of pesticides (LODs below 0.01 mg/kg) in a complex matrix was discussed.     

A sufficient descent LS conjugate gradient method for unconstrained optimization problems

In this paper, we make a modification to the Liu-Storey (LS) conjugate gradient method and propose a descent LS method. The method can generate sufficient descent directions for the objective function. This property is independent of the line search used. We prove that the modified LS method is globally convergent with the strong Wolfe line search. The numerical results show that the proposed descent LS method is efficient for the unconstrained problems in the CUTEr library.     

Quantum-inspired space search algorithm (QSSA) for global numerical optimization

This work presents the evolutionary quantum-inspired space search algorithm (QSSA) for solving numerical optimization problems. In the proposed algorithm, the feasible solution space is decomposed into regions in terms of quantum representation. As the search progresses from one generation to the next, the quantum bits evolve gradually to increase the probability of selecting the regions that render good fitness values. Through the inherent probabilistic mechanism, the QSSA initially behaves as a global search algorithm and gradually evolves into a local search algorithm, yielding a good balance between exploration and exploitation. To prevent a premature convergence and to speed up the overall search speed, an overlapping strategy is also proposed. The QSSA is applied to a series of numerical optimization problems. The experiments show that the results obtained by the QSSA are quite competitive compared to those obtained using state-of-the-art IPOP-CMA-ES and QEA.     

A hybrid trust region algorithm for unconstrained optimization

This paper presents a hybrid trust region algorithm for unconstrained optimization problems. It can be regarded as a combination of ODE-based methods, line search and trust region techniques. A feature of the proposed method is that at each iteration, a system of linear equations is solved only once to obtain a trial step. Further, when the trial step is not accepted, the method performs an inexact line search along it instead of resolving a new linear system. Under reasonable assumptions, the algorithm is proven to be globally and superlinearly convergent. Numerical results are also reported that show the efficiency of this proposed method.