A Study of Model for Distributed Measurement and Control System

This paper is concerned with a method for forming distributed measurement and control system.A three-layer structure model based on network,physical node layer and func-tion node layer is discussed.It is designed on object-oriented software method.The model has a fine application prospect.

Stability and boundedness in terms of two measures for nonlinear impulsive control systems

In this paper we study stability and boundedness in terms of two measures for impulsive control systems. By using variational Lyapunov method, a new variational comparison principle and some criteria on stability and boundedness are obtained. An example is presented to illustrate the efficiency of proposed result.

Design of a Modularized Automatic Measurement and Control System for LaserInduced Breakdown Spectrometer

In order to improve the compatibility of laser-induced breakdown spectroscopy( LIBS) instrument for different types of parts and optimize the analysis and testing processes,a modularized automatic measurement and control system was developed. Based on the characteristics of each LIBS component, the following development steps have been performed:( 1) a summary of characteristic parameters of the component are established;( 2) the integration mechanism of multiple electrical interfaces is designed;( 3) the component control instruction library is developed. The experimental results indicate that the measurement and control system is compatible with most LIBS parts in the market.Spectrometer and laser can be compatible with at least three different types of parts. In addition,a multilayer iterative testing process is designed to improve the efficiency of optimization process of LIBS parameters. The experimental results have shown that the automatic optimization of the delay time compared to the manual testing provides significant gain in testing efficiency. The range of delay time in the experiments is 1. 28 to 10. 28 μs and the step value is 1,0. 5,0. 2 and 0. 1 μs. The gain in testing efficiency has been found to be increased by 73. 76%,75. 93%,78. 81% and 80. 42%,respectively.

Global output feedback control of feedforward nonlinear time-delay systems with unknown growth rate and unknown measurement sensitivity

This paper discusses the problem of global state regulation via output feedback for a class of feedforward nonlinear time-delay systems with unknown measurement sensitivity. Different from previous works, the nonlinear terms are dominated by upper triangular linear unmeasured (delayed) states multiplied by unknown growth rate. The unknown growth rate is composed of an unknown constant, a power function of output, and an input function. Furthermore, due to the measurement uncertainty of the system output, it is more difficult to solve this problem. It is proved that the presented output feedback controller can globally regulate all states of the nonlinear systems using the dynamic gain scaling technique and choosing the appropriate Lyapunov–Krasovskii functionals.

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.

H-infinity measurement-feedback control for discrete-time systems with a single measurement delay

H-infinity control problem for linear discrete-time systems with instantaneous and delayed measurements is studied. A necessary and sufficient condition for the existence of the H-infinity controller is derived by applying reorganized innovation analysis approach in Krein space. The measurement-feedback controller is designed by performing two Riccati equations. The presented approach does not require the state augmentation.

Hydraulic drive and control system of the cone collecting robot

This paper describes the basic structure and design and operation principle of the hydraulic drive and control system with two pumps and two circuits. The manipulator of the cone collecting robot designed is full driven by hydraulic, which has five freedoms. The computer and electrohydraulic proportion velocity regulating valve were installed to realize open loop serve control for reducing cost and easy application.

Advancement in Wide Area Monitoring Protection and Control Using PMU’s Model in MATLAB/SIMULINK

A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.

Comparison and Performance Analysis of FACTs Controller in System Stability

In large inter connected power systems, inter-area oscillations are turned to be a severe problem. Hence inter-area oscillations cause severe problems like damage to generators, reduce the power transfer capability of transmission lines, increase wear and tear on network components, increase line losses etc. This paper is to maintain the stability of system by damping inter-area oscillations. Implementation of new equipment consists of high power electronics based technologies such as FACTs and proper controller design has become an essential to provide better damping performance than Power System Stabilizer (PSS). With development of Wide Area Measurement System (WAMS), remote signals have become as feedback signals to design Wide Area Damping Controller (WADC) for FACTs devices. In this work, POD is applied to both SVC and SSSC. Simulation studies are carried out in Power System Analysis Toolbox (PSAT) environment to evaluate the effectiveness of the FACTs controller in a large area power system. Results show that extensive analysis of FACTs controller for improving stability of system.

Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

This paper studies the consensus control of multiagent systems with binary-valued observations.An algorithm alternating estimation and control is proposed.Each agent estimates the states of its neighbors based on a projected empirical measure method for a holding time.Based on the estimates,each agent designs the consensus control with a constant gain at some skipping time.The states of the system are updated by the designed control,and the estimation and control design will be repeated.For the estimation,the projected empirical measure method is proposed for the binary-valued observations.The algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued observations.And,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’states.Finally,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing literature.Simulations are given to demonstrate the theoretical results.

The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems

For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algorithm is proposed. It is proved that the errors of estimated states and the actual system's states are bounded. And it is guaranteed that the estimated states of the closed-loop system are ultimately bounded in a region containing the origin. As a result, the states of the actual system are ultimately bounded. A simulation example verifies the effectiveness of the proposed distributed control method.

Bayesian Approach to Ranking and Selection for a Binary Measurement System

Binary measurement systems that classify parts as either pass or fail are widely used. Inspectors or inspection systems are often subject to error. The error rates are unlikely to be identical across inspectors. We propose a random effects Bayesian approach to model the error probabilities and overall conforming rate. We also introduce a feature-subset selection procedure to determine the best inspector in terms of overall classification accuracy. We provide simulation studies that demonstrate the viability of our proposed estimation ranking and subset-selection methods and apply the methods to a real data set.

Train crossing modeling based on measurements and best numerical approximation in subway tunnels

Communication based train control systems （CBTC） must work even in the worst situation-- train crossing. This paper models the propagation characteristics in one of the most common and piv- otal scenarios--train crossing in subway tunnels which is rarely mentioned in previous publications. Firstly, measurements for train crossing scenario at 2.4 GHz in a real subway line in Madrid have been made. The field measurement is the most reliable way to reveal the propagation characteristics involving shadowing effect and fast fading. Moreover, to precisely describe the fast fading distribu- tion and eliminate the inevitable weak points of traditional fitting way, a best numerical approxima- tion method using Legendre orthogonal polynomials has been proposed. Comparisons show that this method works better and is of greater physical significance. Finally, a complete statistical model is given and all the coefficients can be applied by system designers for the link and system level simu- lations.

Data-Based Predictive Control for Networked Nonlinear Systems with Packet Dropout and Measurement Noise

In this paper, the data-based control problem is investigated for a class of networked nonlinear systems with measurement noise as well as packet dropouts in the feedback and forward channels. The measurement noise and the number of consecutive packet dropouts in both channels are assumed to be random but bounded. A data-based networked predictive control method is proposed, in which a sequence of control increment predictions are calculated in the controller based on the measured output error, and based on the control increment predictions received by the actuator, a proper control action is obtained and applied to the plant according to the real-time number of consecutive packet dropouts at each sampling instant. Then the stability analysis is performed for the networked closedloop system. Finally, the effectiveness of the proposed method is illustrated by a numerical example.

Reduced Order H_∞/LTR Method for Aeroengine Control System

This paper proposes a new loop recovery method to solve the reduced order problem of H∞/ LTR method. The resulted lower order controller shares almost the same performance and robustness as the original H ∞/LTR controller. Further more, this paper develops a new order reduction method: slow-fast mode order reduction (SFMOR) method. This order reduction method is particularly effective for those controllers whose modes can be divided into a slow part and a fast part according to their velocities. Application of these methods to a benchmark example and a certain turbofan engine is described.

基于Android的茶叶生产线无线智能测控系统研究

针对我国茶叶生产线存在的信息化与智能化水平低、成品茶质量不稳定、生产效率较低等问题,提出了一种茶叶生产线无线智能测控方法,设计了基于Android平台的茶叶生产线的无线智能测控系统。该系统由Android移动客户端、服务器、PLC处理器、各型传感器及生产线成套设备组成,用户通过Android移动客户端登录系统可以实时获取茶叶生产线的生产加工参数,对茶叶生产线的工作参数进行设置调控,实现对茶叶生产线的无线智能化控制。试验表明,该系统可以有效提高茶叶生产线的生产效率,保证成品茶质量的一致性,提高茶叶生产线信息化和智能化水平。

基于Android的分布式数据采集系统设计

随着无线传感网络技术的大量涌现,各种分布式测控系统得到了广泛的应用和研究。针对目前各种测控方法的不同,设计一种基于Android的分布式测控系统。主要论述了基于ZigBee的无线传感器网络,蓝牙通信帧格式,Android分中心数据接收和存储,远程数据上报。通过验证,基于Android的分布式测控系统操作简单,适用性强,能实现对环境信息的实时采集与远程上报,适用于多种特殊环境应用。

Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

Evaluating Watershed Vulnerability in Bernalillo County, New Mexico Using Expert Testimony, Fuzzy Analytic Hierarchy Process, and GIS

Geographic Information System (GIS) software was used to create a watershed vulnerability model for Bernalillo County, New Mexico. Watershed vulnerability was investigated as a function of soil erosion and infiltration criteria: precipitation, land slope, soil erodibility (K-factor), vegetation cover (NDVI), land use, drainage density, saturated hydraulic conductivity, and hydrologic soil group. Respective criteria weights were derived using a Fuzzy Analytic Hierarchy Process (FAHP) supported by expert opinion. A survey of 10 experts, representing New Mexico Institute of Mining and Technology (NMT), the New Mexico Bureau of Geology and Mineral Resources (NMBGMR), and the United States Geologic Survey (USGS), provided model input data for an integrated pair-wise comparison matrix for soil erosion and for infiltration. Individual criteria weights were determined by decomposing the respective fuzzy synthetic extent matrix using the centroid method. GIS layers were then combined based on criteria weights to produce maps of soil erosion potential and infiltration potential. A composite watershed vulnerability map was generated by equal weighting of each input map. Model results were categorized into five vulnerability categories: not vulnerable (N), slightly vulnerable (SV), moderately vulnerable (MV), highly vulnerable (HV), and extremely vulnerable (EV). The resulting FAHP/GIS model was used to generate a watershed vulnerability map of discrete areas in Bernalillo County, which may be vulnerable to stormwater run-off events and soil erosion. Such high volume run-off events can cause erosion damage to property and infrastructure. Alternatively, in areas near urban development, stormwater run-off may contribute non-point-source pollutant contamination of New Mexico’s surface water resources. The most problematic areas in Bernalillo County are present in the Eastern and Northwestern portions. However, less than 1% of the total area lies within the lowest and highest vulnerability categories with the majority centered around moderate vulnerability. The results of the model were compared with a previously published crisp AHP method. Both methods showed similar regional vulnerability trends. This MCDS/GIS approach is intended to provide support to local governments and decision makers in selection of suitable structural or nonstructural stormwater control measures.