state estimation with fading measurements,randomly varying nonlinearities and probabilistic distributed delays

In this paper, the state estimation problem is investigated for a class of discrete‐time stochastic systems in simultaneous presence of three network‐induced phenomena, namely, fading measurements, randomly varying nonlinearities and probabilistic distributed delays. The channel fading is characterized by the ?th‐order Rice fading model whose coefficients are mutually independent random variables with given probability density functions. Two sequences of random variables obeying the Bernoulli distribution are utilized to govern the randomly varying nonlinearities and probabilistic distributed delays. The purpose of the problem addressed is to design an state estimator such that the dynamics of the estimation errors is stochastically stable and the prespecified disturbance rejection attenuation level is guaranteed. Through intensive stochastic analysis, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimization one that can be solved via the semi‐definite program method. Finally, a simulation example is provided to show the usefulness of the proposed state estimation scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

High‐precision formation control of nonlinear multi‐agent systems with switching topologies: A learning approach

Arbitrary high precision is considered one of the most desirable control objectives in the relative formation for many networked industrial applications, such as flying spacecrafts and mobile robots. The main purpose of this paper is to present design guidelines of applying the iterative schemes to develop distributed formation algorithms in order to achieve this control objective. If certain conditions are met, then the control input signals can be learned by the developed algorithms to accomplish the desired formations with arbitrary high precision. The systems under consideration are a class of multi‐agent systems under directed networks with switching topologies. The agents have discrete‐time affine nonlinear dynamics, but their state functions do not need to be identical. It is shown that the learning processes resulting from the relative output formation of multi‐agent systems can converge exponentially fast with the increase of the iteration number. In particular, this work induces a distributed algorithm that can simultaneously achieve the desired relative output formation between agents and regulate the movement of multi‐agent formations as desired along the time axis. The illustrative numerical simulations are finally performed to demonstrate the effectiveness and performance of the proposed distributed formation algorithms. Copyright © 2014 John Wiley & Sons, Ltd.     

Distributed non-cooperative robust MPC based on reduced-order models

In this paper, a non-cooperative distributed MPC algorithm based on reduced order model is proposed to stabilize large-scale systems. The large-scale system consists of a group of interconnected subsystems. Each subsystem can be partitioned into two parts: measurable part, whose states can be directly measured by sensors, and the unmeasurable part. In the online computation phase, only the measurable dynamics of the corresponding subsystem and neighbour-to-neighbour communication are necessary for the local controller design. Satisfaction of the state constraints and the practical stability are guaranteed while the complexity of the optimization problem is reduced. Numerical examples are given to show the effectiveness of this algorithm.     

Energy-efficient control of nanosatellites during distributed region formation flying

In this paper, we present an energy-efficient method for distributed region formation flying of nanosatellites. The proposed framework consists of two concurrent sub-schemes that include estimation and formation. In the estimation sub-scheme, unlike the existing methods on satellite formation flying, that assume the availability of the reference orbital elements to all followers, here, a distributed estimator is developed so that the follower nanosatellites estimate the position of the leader in its orbital slot. In the formation sub-scheme, we consider a region formation strategy which is an efficient method in dealing with the formation of a large number of nanosatellites. We propose an optimal region following formation method based on the receding horizon control (RHC) using the estimated reference orbital elements. Subsequently, an algorithm is presented to solve the proposed energy-efficient formation flying method. Finally, the simulation result is presented that illustrates the purposed method improves the power consumption for each nanosatellite with respect to the existing non-optimal region formation flying controllers.     

Leader-following consensus for uncertain second-order nonlinear multi-agent systems

This paper studies the leader-following consensus problem for a class of second-order nonlinear multi-agent systems subject to linearly parameterized uncertainty and disturbance. The problem is solved by integrating the adaptive control technique and the adaptive distributed observer method. The design procedure is illustrated by an example with a group of Van der Pol oscillators as the followers and a harmonic system as the leader.     

Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

In this paper, a novel framework for networked estimation of multi‐agent systems subject to presence of actuator faults is proposed. This framework is developed based on the notion of sub‐observers where within a group of sub‐observers each sub‐observer estimates certain states that are conditioned on a given input, output, and other state information. We model the overall estimation process by a weighted estimation (WE) digraph. By selecting an appropriate path in the WE digraph, an assigned supervisor can select and configure a set of sub‐observers to successfully estimate all the system states. In the presence of large intermittent disturbances, noise, and faults certain sub‐observers may become invalid, and consequently the supervisor reconfigures the set of sub‐observers by selecting a new path in the estimation digraph such that the impacts of these uncertainties are confined to only the local estimators. This will prevent the propagation of uncertainties on the estimation performance of the entire multi‐agent system. Simulation results provided for a five satellite formation flight system in deep space confirm the validity and applicability of our proposed analytical work.     

基于分布参数的煤矿井下直流杂散电流研究

直流杂散电流是引起井下瓦斯爆炸的重要原因之一,对煤矿安全生产具有很大威胁。针对这一问题,从杂散电流的产生机理着手,建立了井下直流杂散电流的分布参数模型;在该模型的基础上,仿真分析了各个参数对杂散电流的影响,得出了如下结论:随着机车电流的增加、供电区间的延长及轨道电阻的增大,杂散电流也会线性增加,可通过减小机车电流、缩短供电区间长度及减小轨道电阻来减小杂散电流;轨道与大地间过渡电阻低于安全值时会造成杂散电流急剧增大,保证轨道与地之间的绝缘是限制杂散电流的一种有效措施。     

基于PCIe总线接口的EtherCAT从站网卡设计

在基于EtherCAT总线的集散式数据采集系统中,针对测量仪器的高速实时采集需求,设计了一款基于PCIe接口的EtherCAT从站网卡;该网卡将不含网络接口的工控机直接接入EtherCAT网络,从而为浪高、流速、浮体六自由度等物理量的高速实时采集提供了一种简便灵活的实现途径;文中首先介绍了从站网卡的总体结构,接着从硬件和软件两部分详细给出了从站网卡的设计思路,最后通过实验验证了所提方案的有效性;试验结果表明,该从站网卡完全满足对数据传输的实时性、同步性、速度和准确性的要求。     

重复使用运载器预测与健康管理(PHM)技术研究

为了实现传统一次性运载火箭的可重复使用特性,提高重复使用运载器的安全性、可靠性及维修保障性,破解重复使用运载器研制难度大、技术风险高的难题,研究了一种重复使用运载器的预测与健康管理系统方案;该系统采用一种“机载-地面”辅助决策的系统设计方案,机载部分采用分层分布式的系统架构设计方案,地面部分采用区域管理和综合调度的设计方案,有效实现运载器在线式健康状态监测与诊断;重复使用运载器预测与健康管理设计方案的应用,确保运载器在全寿命周期内,实现在线实时故障检测、故障预测和健康评估,为故障处理、维修保障和系统操作优化提供决策支持,显著提升了重复使用运载器的安全性、可靠性、保障性和效费比.     

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.