Applications of Graph Theory to Gross Error Detection for GPS Geodetic Control Networks

This paper describes a broad perspective of the application of graph theory to establishment of GPS control networks whereby the GPS network is considered as a connected and directed graph with three components.In this algorithm the gross error detection is undertaken through loops of different spanning trees using the "Loop Law" in which the individual components Δ X, Δ Y and Δ Z sum up to zero.If the sum of the respective vector components ∑X,∑Y and ∑Z in a loop is not zero and if the error is beyond the tolerable limit (ε>w),it indicates the existence of gross errors in one of the baselines in the loop and therefore the baseline must be removed or re_observed.After successful screening of errors by graph theory,network adjustment can be carried out.In this paper,the GPS data from the control network established as reference system for the HP Dam at Baishan county in Liaoning province is presented to illustrate the algorithm.

STUDY ON INJECTION AND IGNITION CONTROL OF GASOLINE ENGINE BASED ON BP NEURAL NETWORK

According to advantages of neural network and characteristics of operatingprocedures of engine, a new strategy is represented on the control of fuel injection and ignitiontiming of gasoline engine based on improved BP network algorithm. The optimum ignition advance angleand fuel injection pulse band of engine under different speed and load are tested for the samplestraining network, focusing on the study of the design method and procedure of BP neural network inengine injection and ignition control. The results show that artificial neural network technique canmeet the requirement of engine injection and ignition control. The method is feasible for improvingpower performance, economy and emission performances of gasoline engine.

Fuzzy controller design for networked control system with time-variant delays

Networked control system is new hot-point in control engineering. A new delayed model for networked control systems is presented, based on which an LQR controller is designed. A method of delays estimation online is also given. For the difficulty on implementation of LQR in NCSs with time-variant delays, the Mamdani intelligent logic with LQR controller is addressed. The stability of the networked control system is also given. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.

Multivariable Nonlinear Proportional-Integral-Derivative Decoupling Control Based on Recurrent Neural Networks

A nonlinear proportional-integral-derivative (PID) controller is constructed based on recurrent neural networks. In the control process of nonlinear multivariable systems, several nonlinear PID controllers have been adopted in parallel. Under the decoupling cost function, a decoupling control strategy is proposed. Then the stability condition of the controller is presented based on the Lyapunov theory. Simulation examples are given to show effectiveness of the proposed decoupling control.

Adaptive Air-Fuel Ratio Control with MLP Network

This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC. Keywords Air-fuel ratio control - IC engine - adaptive neural networks - nonlinear programming - model predictive control Shi-Wei Wang PhD student, Liverpool John Moores University; MSc in Control Systems, University of Sheffield, 2003; BEng in Automatic Technology, Jilin University, 2000; Current research interests automotive engine control, model predictive control, sliding mode control, neural networks.Ding-Li Yu obtained B.Eng from Harbin Civil Engineering College, Harbin, China in 1981, M.Sc from Jilin University of Technology, Changchun, China in 1986 and PhD from Coventry University, U.K. in 1995, all in control engineering. He is currently a Reader in Process Control at Liverpool John Moores University, U.K. His current research interests are in process control, engine control, fault detection and adaptive neural nets. He is a member of SAFEPROCESS TC in IFAC and an associate editor of the IJMIC and the IJISS.

Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks

An adaptive inverse controller for nonliear discrete-time system is proposed in this paper. A compound neural network is constructed to identify the nonlinear system, which includes a linear part to approximate the nonlinear system and a recurrent neural network to minimize the difference between the linear model and the real nonlinear system. Because the current control input is not included in the input vector of recurrent neural network (RNN), the inverse control law can be calculated directly. This scheme can be used in real-time nonlinear single-input single-output (SISO) and multi-input multi-output (MIMO) system control with less computation work. Simulation studies have shown that this scheme is simple and affects good control accuracy and robustness.

Engineering coordinate system for vertical mine region based on GPS technique

For the problems existing in control network of vertical mine region established by conventional way, this paper advances a new scheme of establishing engineering coordinate system for vertical mine region. Based on the GPS positioning technique, through the relationship of coordinate transformation about a group of connecting points, the transforming parameters between the WGS-84 system and the Beijing54 system or Xi’an80 system about the region were calculated. The plane coordinate systems about the region can be maintained with a few of GPS control points using the method of GPS level, and fits the quasi-geoid about the region based on the Ellipsoid WGS-84. Huanghai Vertical Datum 1985 about the region can be maintained with the Ellipsoid WGS-84 as datum plane. Practice proves that there are advantages using the scheme to establish engineering coordinate system: the coordinate system as engineering foundation for vertical mine region will be in preservation for a long time; it is convenient and easy to carry out daily surveying work based on this coordinate system.

跨海桥梁首级GPS控制网数据处理方法及应用

跨海桥梁具有跨海距离长、工程环境恶劣、施工周期长、精度要求高等显著特点,对工程施工控制网测量提出了较高要求。以平潭海峡公铁大桥首级GPS控制网为例,研究并提出适合于跨海桥梁首级GPS控制网的高精度大规模工程控制网数据处理方法,并采用实测数据进行分析论证。结果表明,使用国际公认的高精度数据处理软件GAMIT,采用合适的模型和参数对多时段长时间的同步观测数据进行精细处理后,可获得高质量的基线向量解。在网平差阶段,引入一种基于相关分析的粗差探测及处理方法,对大于三倍基线中误差的小粗差基线进行探测和分析处理,可进一步提高首级GPS控制网的成果精度。

GPS-RTK测量技术在水利工程测绘中的运用

GPS-RTK测量技术属于现代化工程测量技术,具有定位准确、操作便捷的特性,所提供的是三维立体坐标,可一体化完成控制测量、工程放样、数字地图绘制等多项任务。为进一步明确水利工程测绘中GPSRTK测量技术的应用方法与价值效用,首先介绍了水利工程测绘中的GPS-RTK测量技术,其次结合工程实例探讨了GPS-RTK测量技术的实践应用方法。旨在为水利工程测绘中科学应用此技术提供参考。

水利工程GPS静态测量控制网布设技术与测量精度研究

文章通过对GPS静态测量控制网的布设技术进行深入分析,分析各项技术参数对测量精度的影响,进而优化网络设计,确保水利工程在空间位置信息方面的准确性。通过对起始数据的校核处理及对各项技术参数的细致研究,有效提高水利工程中GPS测量的准确性,为工程建设提供可靠的空间位置信息支持。此研究为水利工程测量提供了指导意义,对其他领域的精密测量和空间信息获取也具有借鉴价值。

2000国家GPS大地控制网的数据处理和精度评估

2000国家GPS大地控制网集合了各类GPS网近10年的观测数据,提供GPS点在全球参考框架下2000.0历元的绝对位置.文中简要介绍GPS数据处理的方法,给出数据处理的精度统计;以部分点的实测速度为基础,建立中国大陆地壳运动速度场;基于GPS测量的动态系统状态,选择序贯卡尔曼滤波的广义测量平差方法,对GPS点做顾及地壳运动的整网平差,并给出整网平差结果的精度统计和外部检核.一系列的手段和措施保证了平差结果的合理性和可靠性.

GPS测量实践教学的尝试

卫星导航定位已成为现代测绘工程领域的一种重要测量技术手段,为了满足测绘工程专业人才培养的需要,结合学校地理环境开展有针对性的GPS测量实践教学活动,使学生在规范的教学实习场地,领受到实际工程作业的氛围。论述了GPS实践教学基准网的布设以及模拟工程施工控制网和变形监测网的GPS实习情况。几年来的实践教学成效明显,深受学生好评。

特大型桥梁施工GPS高程控制网技术研究

探索了采用GPS技术建立桥梁施工高程控制网的难点及关键问题,分析了GPS跨河高程传递测量方法的技术要点,结合工程实例得出了一些结论和建议。

关于国家高精度GPS B级网成果的使用问题

本文简要地介绍了国家高精度GPS网[1]情况,对GPSB级网与2000国家GPS大地控制网[3]重合点的成果进行了比较与分析,在2000国家大地坐标系下,如何处理以B网成果为基准建立的GPSC级网或城市基础控制网成果问题进行了讨论,提出了解决办法,并进行了试算、分析和比较。

2000国家GPS大地控制网数据处理方法与结果

介绍了我国GPS大地控制网的基本情况 ,阐述了结合地壳运动观测网络工程建立全国统一的“2 0 0 0国家GPS大地控制网”的意义 ,并介绍了整网平差中采用的技术方法和最后平差结果及精度。

基于径向基函数神经网络的GPS高程转换方法

针对GPS高程与正常高程的转换问题,给出了基于径向基函数(Radial Basis Function,RBF)神经网络的模型。该模型隐含层选用Gauss函数作为基函数,学习算法采用自组织选取中心法策略。用实际观测数据进行了试验和仿真,结果表明,用RBF神经网络转换GPS高程的精度优于最小二乘法。对RBF神经网络方法和反向传播(Back-Propagation,BP)神经网络方法转换GPS高程的精度进行了比较,虽然两种方法的结果相近,但RBF神经网络方法在学习速度方面远比BP神经网络方法快。由此可见,RBF神经网络方法用于转换GPS高程是可行和有效的。

从GPS定位技术的发展谈《控制测量学》课程的改革

随着GPS定位技术的日益成熟,传统的大地测量平面控制网的建立方法,正逐步被GPS控制网的建立方法所取代。介绍了《控制测量学》课程改革的若干建议。

GPS技术在成都市地铁建设中的应用

介绍了成都市地铁一号线GPS控制网的布设、精度设计、观测方法等,就GPS技术在城市地铁建设中的应用提出几点建议。

城市GPS控制网工程研究

通过应用GPS技术改造城市基本控制网工程实例,在控制点的布设、网型结构、精度统计、成果与原城市控制成果的一致性等方面进行了实验研究,提出了科学实用的工程技术方案;在水准高程与GPS拟合高程和RTK高程成果进行对比分析的基础上,认为GPS拟合高程和RTK高程成果不能作为城市基本高程控制网成果使用,需要单独布设水准网。

公路控制测量中GPS坐标向国家坐标转换的三维分离回归法

为了克服在公路勘测领域将GPS坐标转换为国家坐标(地方坐标、线路坐标)的传统方法的两个缺陷(一个是转换精度不高,另一个是极易出现病态矩阵),采用了将三维坐标(X,Y,Z)分开转换的策略(三维分离回归法),介绍了三维分离回归法的基本思想、转换过程及转换实例,在分开转换的过程中应用了多元线性回归理论。三维分离回归法的实际应用显示该方法确实能够克服转换中的病态矩阵问题,使三雏转换精度提高一倍。理论和实践均证明,三维分离回归法适用于GPS坐标向国家坐标的转换。