一种基于加速度计和天文的卫星自主导航新方法

直接敏感地平是一种典型自主天文导航方法,该方法简单可靠,易于实现,但是由于常用卫星轨道动力学J2模型精度有限,地球敏感器精度较低,因此导航精度不高。加速度计是测量运载体线加速度的常用惯性导航设备,当航天器在轨运行时,星载加速度计能够测量航天器所受发散力。结合上述两种方法的特点,提出一种将加速度计和天文相结合的自主天文导航新方法。在常用卫星轨道动力学模型基础上,引入大气阻力和太阳光压系数模型作为自主导航系统状态方程的一部分,并建立近地空间环境下星载加速度计的测量模型,将其与直接敏感地平均作为导航系统观测方程。设计基于信息融合的自主导航滤波方法,通过对多种导航模式进行数值仿真及结果分析,结果表明所设计方法提高了系统定位精度62.8%和速度精度63.9%,增强了系统可靠性。     

Modelling,Synthesis, and Simulation of Supervisory Process Control Systems

Modelling, synthesis, and simulation issues of the supervisory systems in process control are investigated in the paper. Petri nets are used as a basic modelling framework for the supervisory part of the system. It is shown how the final verification effort can be minimised by applying formal synthesis methods. A straightforward approach to the industrial implementation of the developed solutions is suggested by means of sequential function chart representation. A batch process cell case study is used to illustrate the described concepts. Corresponding continuous and discrete event models of the process cell units are developed and a co-ordinating supervisor is designed by the method of place invariants. The system is simulated by the continuous simulation tool Matlab-Simulink, which is enhanced for simulation of the sequential control logic represented by sequential function chart.     

Small Periodic Solutions Generated by Sublinear Terms

The paper is concerned with Hopf bifurcations in systems of autonomous ordinary differential equations with a parameter. The principal distinction between usual theorems on Hopf bifurcations and our results is that here the linearized equation is degenerate and independent of the parameter. We present sufficient conditions for a parameter value to be a bifurcation point and analyze properties of small cycles arising in the vicinity of the equilibrium. Sublinear nonlinearities play the main role in the results obtained.     

驾驶员可靠性筛选数学模型分析

利用随机分组测试理论和算法,建立了汽车驾驶员安全可靠性筛选的定量分析数学模型,在统计分析观察时间段的基础上,可以筛选出安全可靠的驾驶员,驾驶员年龄段,为选拔汽车驾驶员,提高驾驶员素质,防止人为差错导致交通事故,提供理论依据.     

A gravity driven micro flow injection wetting film extraction system on a polycarbonate chip

A micro flow injection wetting film liquid-liquid extraction system has been developed for trace analyte concentration and on-chip detection. A hydrophobic channel fabricated on a polycarbonate chip was used to support the wetting film, and hydrostatic pressure generated by the difference in liquid levels was employed to drive the fluids. Sequential injection of segments of aqueous sample solution and organic solvent was conducted by switching the sample- or solvent-containing vials to an on-chip sampling probe, and detection was performed by a co-focused, laser induced fluorescence detector. Using butyl rhodamine B as a model analyte and butanol as the solvent for both film-coating and elution, various experimental conditions such as hydrostatic pressure, coating time, channel length, sampling volume, and sample acidity were investigated. Under optimized conditions, a 24-fold enrichment factor was obtained with the consumption of about 3 μL sample solution, and a detection limit (3σ) of 6.0 × 10⁻⁹ M butyl rhodamine B was achieved at the sampling rate of 19 h⁻¹. Eleven consecutive runs of a 1.0 × 10⁻⁵ M butyl rhodamine B solution produced a relative standard deviation of 1.5% for the detected fluorescence signals.     

Study on autonomous navigation based on pulsar timing model

The basic principle of pulsar timing model was introduced, and the general relativistic corrections were analyzed when pulse time of arrival (TOA) was transferred to coordinate TOA at the Solar System Barycentre. Based on the shifting, an iterative method of autonomous position determination for spacecraft was developed. Accordingly, the linear form of the position offset equation was evolved. Using the initial estimated value of spacecraft’s position as the input of pulsar timing equation, through calculation of the offset between measured or transferred and predicted TOA, the position offset can be solved by Least Squares. At last, the main error sources including modeling error and parameters error were discussed. Supported by the National Defence Laboratory Foundation of China (Grant No. 9140C3601010901) and Science Foundation of Shaanxi Province (Grant No. 2007F12) and the Technology Specialism Foundation of Shaanxi Education Department of Shaanxi Province (Grant No. 07JK332), and the Innovative Research Plan of Xi’an University of Technology (Grant No. 105-210714)     

Attractive target wave patterns in complex networks consisting of excitable nodes

This review describes the investigations of oscillatory complex networks consisting of excitable nodes,focusing on the target wave patterns or say the target wave attractors.A method of dominant phase advanced driving(DPAD) is introduced to reveal the dynamic structures in the networks supporting oscillations,such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks.The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns.Therefore,the center(say node A) and its driver(say node B) of a target wave can be used as a label,(A,B),of the given target pattern.The label can give a clue to conveniently retrieve,suppress,and control the target waves.Statistical investigations,both theoretically from the label analysis and numerically from direct simulations of network dynamics,show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large,and all these attractors can be labeled and easily controlled based on the information given by the labels.The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.     

Association Constant Prediction for the Inclusion of α-Cyclodextrin with Benzene Derivatives by an Artificial Neural Network

The association constants (K_a) for the inclusion complexation of -cyclodextrin (-CD) with 72 mono- and 1,4-disubstituted benzenes were predicted successfully by an artificial neural network (ANN) with molar refraction (R_m) and hydrophobic constant () as input parameters, which reflect the volume and hydrophobicity of the substituents respectively. The predictions strongly suggested that the inclusion complexation of -CD with guest molecules was mainly driven by van der Waals forces and hydrophobic interactions