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2016 International Conference on Control, Automation and Information Sciences (ICCAIS)最新文献

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Control with general dissipativity constraint and non-monotonic Lyapunov functions 具有一般耗散约束和非单调Lyapunov函数的控制
T. Tran, J. Maciejowski
In this paper, a new framework for constructing discrete-time control systems with non-monotonic Lyapunov functions and General Dissipativity Constraint (GDC) is developed as an alternative to the small gain design that may become conservative in some decentralized control applications. The GDC Lyapunov function in this approach is nonmonotonic since its incremental difference is essentially nonnegative. Possessing the advantages of an input and output approach, the presented GDC is suitable for the control problem of heterogeneous interconnected systems that have complex interactions between subsystems, such as power systems or networked robotics.
本文提出了一种构造具有非单调李雅普诺夫函数和一般耗散性约束(GDC)的离散时间控制系统的新框架,以替代在某些分散控制应用中可能变得保守的小增益设计。这种方法中的GDC Lyapunov函数是非单调的,因为它的增量差分本质上是非负的。该方法具有输入输出方法的优点,适用于子系统之间具有复杂交互作用的异构互联系统的控制问题,如电力系统或网络机器人。
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引用次数: 5
Multi-agent coordination using limit cycles in dynamic environment 动态环境下基于极限环的多智能体协调
Sajjad Manzoor, Youngjin Choi
The paper presents a novel neural oscillator-based limit cycle approach for multiple robots formation and navigation. A group of point-robots is directed to move towards a target as well as to form a circular shape surrounding it. Initially the algorithm for a stationary target in absence of obstacle is developed, and then it is extended to dynamic target and further to an obstacle avoidance including static and dynamic obstacles. An attraction property of neural oscillator-based limit cycle is used for the robots to move towards circle around target with an arbitrary radius. The group of pursuing robots reaches the target in such a way that they remain at a desired distance from it keeping equally distributed angle around it. Another finding is that a change of communication (or sensor) matrix makes a transient formation to be different, though the final shape remains the same. Finally, the effectiveness of the proposed method is verified through several simulations.
提出了一种新的基于神经振荡器的多机器人编队与导航极限环方法。一组点机器人被引导向目标移动,并在目标周围形成一个圆形。首先研究了无障碍物静止目标的避障算法,然后将其推广到动态目标,进而推广到包括静态和动态障碍物的避障算法。利用神经振荡器极限环的吸引特性,使机器人能够绕任意半径的目标进行圆周运动。一组追逐的机器人以这样一种方式到达目标,即它们与目标保持期望的距离,并保持围绕目标的均匀分布角度。另一个发现是,通信(或传感器)矩阵的变化会使瞬态形成不同,尽管最终形状保持不变。最后,通过仿真验证了所提方法的有效性。
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引用次数: 1
Multi-task firework algorithm for cell tracking and contour estimation 多任务烟花细胞跟踪和轮廓估计算法
Jian Shi, Benlian Xu, Peiyi Zhu, Mingli Lu
Dynamics analysis of cells' lifecycle progression is essential in medical research. Multiple cells tracking through fluorescence microscopy imaging is often challenged by many roadblocks including the severe image noise and clutter, the occlusion and adhesion among cells, and the low resolution and contrast of image. To gain full dynamics of multiple cells, a novel multi-task firework explosion based tracking algorithm is proposed for multiple cells tracking in low contract image sequences in this paper. A conventional firework algorithm is used to determine the cell location, and a simplified firework explosion searching strategy is then adopted to estimate the cell contour. Simulation results verify the effectiveness of the methods.
细胞生命周期过程的动力学分析在医学研究中是必不可少的。荧光显微镜成像中多细胞的跟踪常常面临图像噪声和杂波严重、细胞间的遮挡和粘附、图像分辨率和对比度低等障碍。为了获得多细胞的完整动态,提出了一种基于烟花爆炸的多任务跟踪算法,用于低收缩图像序列中的多细胞跟踪。采用传统的烟花算法确定细胞位置,然后采用简化的烟花爆炸搜索策略估计细胞轮廓。仿真结果验证了该方法的有效性。
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引用次数: 4
Inertial navigation system positioning assisted by star sensor 星敏感器辅助惯性导航系统定位
Hongsong Du, Qian Sun, Ya Zhang, Zhao Qi, Yaoyao Wen
The Star Sensor can be used to assist the inertial navigation system (INS) for navigation and positioning, restraining the accumulated error caused by the inertial components. During the integrated navigation process, the Star Sensor is installed above the INS, generated installation errors between the INS body coordinate system and the Star Sensor body coordinate system. In order to increase the system accuracy, a new gyro error model is established in this paper which taken full account of various error factors. The gyro drifts and the gyro errors coefficients are considered as the state variables. The attitude information of Star Sensor is used as the high-accurate information to construct the observation with the attitude information of INS. Taken the nonlinearity of the actual system into account, the nonlinear filter Cubature Kalman Filter (CKF) is used to estimate the gyro errors commendably. The experiment results showed that the positioning error reduced a lot by utilizing this novel method.
星敏感器可用于辅助惯性导航系统进行导航定位,抑制惯性分量引起的累积误差。在组合导航过程中,星敏感器安装在惯导系统上方,会产生惯导系统主体坐标系与星敏感器主体坐标系之间的安装误差。为了提高系统精度,本文建立了一种充分考虑各种误差因素的陀螺误差模型。将陀螺漂移和陀螺误差系数作为状态变量。利用星敏感器的姿态信息作为高精度信息,与惯导系统的姿态信息构建观测。考虑到实际系统的非线性特性,采用非线性库伯卡尔曼滤波(cuature Kalman filter, CKF)对陀螺误差进行了较好的估计。实验结果表明,该方法大大降低了定位误差。
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引用次数: 3
Efficient implementation of maximization likelihood estimation to constrained measurement random latency probability in nonlinear system 非线性系统中约束测量随机延迟概率最大化似然估计的有效实现
Xiaoxu Wang, Qianyun Zhang, Yan Liang, Feng Yang, Q. Pan, Lin Li
This paper focuses on quickly identifying the unknown or time-varying random latency probability (RLP) of the measurements in the nonlinear networked multi-sensor system by resorting to the efficient implementation of maximization likelihood (ML) estimation. Firstly, the full-probability likelihood computation is equivalently transformed into a log-likelihood function summation form parameterized by RLP through Bayes' rule. Secondly, the computation of the log-likelihood function is further transferred by skillfully introducing Jensen's inequality for facilitating the rapid maximization. Thirdly, the simple identification result of RLP is obtained by constructing Lagrange operator to maximize the transferred log-likelihood with the RLP parameter constraint. Finally, an example motivated by the maneuvering target tracking application is presented to demonstrate the superiority of the new method.
本文的重点是通过有效地实现最大似然估计,快速识别非线性网络化多传感器系统中测量值的未知或时变随机延迟概率。首先,通过贝叶斯规则将全概率似然计算等效转化为RLP参数化的对数似然函数求和形式;其次,通过巧妙地引入Jensen不等式,进一步转移对数似然函数的计算,使其快速最大化。第三,在RLP参数约束下,构造拉格朗日算子使传递对数似然最大化,得到简单的RLP识别结果。最后,以机动目标跟踪应用为例,验证了该方法的优越性。
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引用次数: 0
Flight testing of control allocation for elevator actuator fault in small UAV 小型无人机电梯执行器故障控制分配飞行试验
Z. Sahwee, Aina Suriani Mahmood, N. A. Rahman, K. Sahari
Final validation of new control technique for any air vehicle must be conducted through flight testing. It is the most critical phase of the research work where it validates and provides real world feedback on the theoretical and simulation design. On the other hand, an unmanned aircraft as presented in this work is highly complex systems; a single component failure can lead to potentially dangerous consequences. The objective of this paper is to present the flight test result on the investigation on using alternate control surface for a control allocation of pitch control transition from elevator to stabilator of a small UAV. There were fourty flight tests have been performed and from the analysis, the proposed method is feasible to be used without affecting flight endurance and characteristics during flight control transition. The alternate control surface accommodation technique proves to promise higher reliability in case of faulty on-board actuator.
任何飞行器的新控制技术的最终验证都必须经过飞行试验。这是研究工作中最关键的阶段,它验证并提供理论和仿真设计的真实世界反馈。另一方面,在这项工作中提出的无人驾驶飞机是高度复杂的系统;单个组件的故障可能导致潜在的危险后果。给出了利用交替控制面进行小型无人机升降舵到稳定器俯仰控制转换控制分配研究的飞行试验结果。进行了40次飞行试验,分析结果表明,该方法在不影响飞控过渡飞行续航力和飞行特性的情况下是可行的。实践证明,交替控制面调节技术在车载执行机构发生故障时具有较高的可靠性。
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引用次数: 3
Combining sparse appearance and Bayesian inference models for object tracking 结合稀疏外观和贝叶斯推理模型的目标跟踪
Zhengqiang Jiang, Benlian Xu, Shengrong Gong
In this paper, we present a method that combines a sparse appearance model into the Bayesian inference framework for tracking pedestrians in video sequences captured by a fixed camera. We formulate sparse appearance model as a linear combination of a set of 4D smoothed colour histograms for each pedestrian. These colour histograms are computed for all detection windows with different confidence values from human detector proposed by Dalal and Triggs. Object tracking is carried out using the Bayesian inference method. For occlusion handling, we integrate the Kalman filter to get the potential region containing target's observation and then use maximum a posteriori estimation to get the most likely observation. We test our tracking method on the benchmark video datasets. Our experimental results show that our tracking method outperforms one without using occlusion handling technique and can handle partial occlusion and false negative errors from human detector.
在本文中,我们提出了一种将稀疏外观模型与贝叶斯推理框架相结合的方法,用于跟踪固定摄像机拍摄的视频序列中的行人。我们将稀疏外观模型表述为每个行人的一组4D平滑颜色直方图的线性组合。这些颜色直方图计算了所有检测窗口的不同置信值从人类检测器提出的Dalal和Triggs。目标跟踪采用贝叶斯推理方法。在遮挡处理中,我们通过卡尔曼滤波得到包含目标观测值的潜在区域,然后使用最大后验估计得到最可能的观测值。我们在基准视频数据集上测试了我们的跟踪方法。实验结果表明,我们的跟踪方法优于不使用遮挡处理技术的跟踪方法,可以处理人类检测器的部分遮挡和假阴性误差。
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引用次数: 0
Track level fusion with an estimation of maximum bound of unknown correlation 基于未知相关最大界估计的航迹级融合
Muhammad Abu Bakr, Sukhan Lee
In distributed fusion architecture, processed information in the form of tracked object data is available instead of raw sensor data. Ignoring the cross-correlation in distributed systems by employing Kalman filter in general leads to inconsistent results. Covariance intersection, on the other hand provide conservative results by overestimating the intersection of individual covariances. In this paper, we present a track level fusion by analytically computing the mean and covariance of fused data under unknown correlation. Unlike the covariance intersection method that searches for a minimum overestimate iteratively, the proposed method finds the maximum covariance under unknown correlation. Furthermore, it is proved that the proposed method provides an exact and consistent result in terms of Bar-Shalom Campo (BC) formula. To show the effectiveness of the proposed method, simulation results of Track-to-Track fusion are provided.
在分布式融合体系结构中,可以利用跟踪目标数据形式的处理信息代替原始传感器数据。在分布式系统中,采用卡尔曼滤波忽略相互关系通常会导致结果不一致。另一方面,协方差相交通过高估个体协方差相交提供保守结果。本文通过分析计算未知相关下融合数据的均值和协方差,提出了一种航迹级融合。与协方差相交法迭代寻找最小过估值不同,该方法在未知相关条件下寻找最大协方差。此外,还证明了该方法对于Bar-Shalom Campo (BC)公式具有精确一致的结果。为了验证该方法的有效性,给出了航迹到航迹融合的仿真结果。
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引用次数: 3
Fault diagnosis of diesel engine lubrication system based on PSO-SVM and centroid location algorithm 基于PSO-SVM和质心定位算法的柴油机润滑系统故障诊断
Yingmin Wang, T. Cui, Fujun Zhang, TianPu Dong, Shen Li
Fault of diesel engine lubrication system will affect engine performance, and diesel engine operation parameters reflect the working state of the engine. In this paper, a data-driven fault diagnosis is proposed using engine real working data. Considering the randomness and instability of the oil pressure in the lubrication system, a fault diagnosis method based on PSO-SVM model and centroid location algorithm is presented. Firstly, fault features are extracted analyzing the data in normal condition. Secondly, particle swarm optimization (PSO) algorithm is used to search the best parameters of support vector machine (SVM) to establish the model of fault diagnosis. Then, support vector machine classification interface is fitted to a curve, and the boundary conditions of fault diagnosis are obtained. Finally, the typical faults of diesel engine lubrication system are diagnosed by the proposed fault diagnosis algorithm. The results show that he proposed PSO-SVM model achieved above 95% classification accuracy; and two typical lubrication system faults of diesel engine can be diagnosed based on the proposed diagnosis method.
柴油机润滑系统的故障会影响发动机的性能,柴油机的运行参数反映了发动机的工作状态。本文提出了一种基于发动机实际工作数据的数据驱动故障诊断方法。针对润滑系统油压的随机性和不稳定性,提出了一种基于PSO-SVM模型和质心定位算法的故障诊断方法。首先,对正常情况下的数据进行分析,提取故障特征;其次,利用粒子群优化(PSO)算法搜索支持向量机(SVM)的最佳参数,建立故障诊断模型;然后,将支持向量机分类界面拟合到曲线上,得到故障诊断的边界条件;最后,利用所提出的故障诊断算法对柴油机润滑系统的典型故障进行了诊断。结果表明,所提出的PSO-SVM模型的分类准确率达到95%以上;并利用该诊断方法对两种典型的柴油机润滑系统故障进行了诊断。
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引用次数: 7
A private machine-cloud architecture and self-reliant controllers for operational technology systems 一个私有的机器云架构和独立的操作技术系统控制器
T. Tran
A private machine-cloud architecture and the associated Self-reliant Control System (SCS) for industrial applications are presented in this paper. The machine-to-machine (M2M) IP-based local area network creates a backbone for the proposed architecture, in which the traditional analogue input and output (I/O) or field-bus subsystems of a traditional process control system are not required. The proposed architecture is not only applicable to a large processing plant, but can also be deployed to the generic feedback control installations, including micro-grids in a power system. The quantitative reliability of the new system is achieved by the fault-tolerant structure of multiple processors via the M2M connectivity. Each processor is a computational platform for multiple feedback control algorithms, functioning in a self-reliant manner. As a result, the amount of data required to be exchanged between processors is kept to minimal. The congregation of these processors and the private M2M local area network form a ‘private machine cloud’ for the SCSs.
本文提出了一种用于工业应用的私有机器云架构和相关的自力控制系统(SCS)。基于ip的机器对机器(M2M)局域网为所提出的体系结构创建了一个主干,在这个主干中不需要传统过程控制系统的传统模拟输入和输出(I/O)或现场总线子系统。所提出的架构不仅适用于大型加工厂,也可以部署到一般的反馈控制装置,包括电力系统中的微电网。新系统的定量可靠性是通过M2M连接的多处理器容错结构来实现的。每个处理器都是多个反馈控制算法的计算平台,以自力更生的方式运作。因此,需要在处理器之间交换的数据量保持在最低限度。这些处理器和专用M2M局域网的集合形成了scs的“专用机器云”。
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引用次数: 1
期刊
2016 International Conference on Control, Automation and Information Sciences (ICCAIS)
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