一种基于并行化方法的自适应光学闭环预测控制器

自适应光学系统的性能受限于伺服系统的延迟误差和波前传感器的光电子噪声。提出了一种多模型单变量预测模型,该模型采用基于Levenberg-Marquardt学习算法的前馈型神经网络。利用计算机多核处理器,设计了一个具有并行处理能力的预测控制器,来实现对自适应光学闭环控制电压的预测,以消除延迟误差的影响。通过数值仿真实验,研究了预测控制器对控制电压和远场斯特雷尔比的影响,与未采用预测控制器的系统进行了比较,并对预测算法的并行性能进行了分析。实验结果表明,使用并行化方法的预测控制器可以有效缩短系统的预测时间,提高预测算法的加速比,与经典比例积分(PI)控制算法相比可以更有效地降低系统由于伺服延迟引起的误差,远场的斯特雷尔比有明显地提高。     

Design and analysis of hybrid metaheuristics for the Reliability p-Median Problem

In the p-Median Problem, it is assumed that, once the facilities are opened, they may not fail. In practice some of the facilities may become unavailable due to several factors. In the Reliability p-Median Problem some of the facilities may not be operative during certain periods. The objective now is to find facility locations that are both inexpensive and also reliable. We present different configurations of two hybrid metaheuristics to solve the problem, a genetic algorithm and a scatter search approach. We have carried out an extensive computational experiment to study the performance of the algorithms and compare its efficiency solving well-known benchmark instances.     

Handling equality constraints in evolutionary optimization

Over the last few decades several methods have been proposed for handling functional constraints while solving optimization problems using evolutionary algorithms (EAs). However, the presence of equality constraints makes the feasible space very small compared to the entire search space. As a consequence, the handling of equality constraints has long been a difficult issue for evolutionary optimization methods. This paper presents a Hybrid Evolutionary Algorithm (HEA) for solving optimization problems with both equality and inequality constraints. In HEA, we propose a new local search technique with special emphasis on equality constraints. The basic concept of the new technique is to reach a point on the equality constraint from the current position of an individual solution, and then explore on the constraint landscape. We believe this new concept will influence the future research direction for constrained optimization using population based algorithms. The proposed algorithm is tested on a set of standard benchmark problems. The results show that the proposed technique works very well on those benchmark problems.     

Computational approach to structural identification of phospholipids using raw mass spectra from nanoflow liquid chromatography–electrospray ionization–tandem mass spectrometry

A qualitative analysis tool (LiPilot) for identifying phospholipids (PLs), including lysophospholipids (LPLs), from biological mixtures is introduced. The developed algorithm utilizes raw data obtained from nanoflow liquid chromatography–electrospray ionization–tandem mass spectrometry experiments of lipid mixture samples including retention time and m/z values of precursor and fragment ions from data‐dependent, collision‐induced dissociation. Library files based on typical fragmentation patterns of PLs generated with an LTQ‐Velos ion trap mass spectrometer are used to identify PL or LPL species by comparing experimental fragment ions with typical fragment ions in the library file. Identification is aided by calculating a confidence score developed in our laboratory to maximize identification efficiency. Analysis includes the influence of total ion intensities of matched and unmatched fragment ions, the difference in m/z values between observed and theoretical fragment ions, and a weighting factor used to differentiate regioisomers through data filtration. The present study focused on targeted identification of particular PL classes. The identification software was evaluated using a mixture of 24 PL and LPL standards. The software was further tested with a human urinary PL mixture sample, with 93 PLs and 22 LPLs identified. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling and mathematical results arising from ferromagnetic problems

In this article,we investigate the equations of magnetostatics for a configuration where a ferromagnetic material occupies a bounded domain and is surrounded by vacuum.Furthermore,the ferromagnetic law takes the form B=μ0μr(|H|)H,i.e.,the magnetizing field H and the magnetic induction B are collinear,but the relative permeability μr is allowed to depend on the modulus of H.We prove the well-posedness of the magnetostatic problem under suitable convexity assumptions,and the convergence of several iterative methods,both for the original problem set in the Beppo-Levi space W1(R3),and for a finite-dimensional approximation.The theoretical results are illustrated by numerical examples,which capture the known physical phenomena.     

Adaptive synchronization of chaos in permanent magnet synchronous motors based on passivity theory

An adaptive synchronization control method is proposed for chaotic permanent magnet synchronous motors based on the property of a passive system.We prove that the controller makes the synchronization error system between the driving and the response systems not only passive but also asymptotically stable.The simulation results show that the proposed method is effective and robust against uncertainties in the systemic parameters.     

Adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions

<正>The adaptive generalized matrix projective lag synchronization between two different complex networks with non-identical nodes and different dimensions is investigated in this paper.Based on Lyapunov stability theory and Barbalat’s lemma,generalized matrix projective lag synchronization criteria are derived by using the adaptive control method.Furthermore,each network can be undirected or directed,connected or disconnected,and nodes in either network may have identical or different dynamics.The proposed strategy is applicable to almost all kinds of complex networks.In addition,numerical simulation results are presented to illustrate the effectiveness of this method,showing that the synchronization speed is sensitively influenced by the adaptive law strength,the network size,and the network topological structure.     

Solving Delay Differential Equations Through RBF Collocation

A general and easy-to-code numerical method based on radial basis functions (RBFs) collocation is proposed for the solution of delay differential equations (DDEs). It relies on the interpolation properties of infinitely smooth RBFs, which allow for a large accuracy over a scattered and relatively small discretization support. Hardy's multiquadric is chosen as RBF and combined with the Residual Subsampling Algorithm of Driscoll and Heryudono for support adaptivity. The performance of the method is very satisfactory, as demonstrated over a cross-section of benchmark DDEs, and by comparison with existing general-purpose and specialized numerical schemes for DDEs.     

On Convergence of a Least-Squares Kansa's Method for the Modified Helmholtz Equations

We analyze a least-squares asymmetric radial basis function collocation method for solving the modified Helmholtz equations. In the theoretical part, we proved the convergence of the proposed method providing that the collocation points are sufficiently dense. For numerical verification, direct solver and a subspace selection process for the trial space (the so-called adaptive greedy algorithm) is employed, respectively, for small and large scale problems.