Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems

This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid. First, a smart grid discrete system model is established in view of D-LAAs. Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid. The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack). A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs. Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks. Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations.     

Adaptive force–environment estimator for manipulators based on adaptive wavelet neural network

This study focuses on the accurate tracking control and sensorless estimation of external force disturbances on robot manipulators. The proposed approach is based on an adaptive Wavelet Neural Network (WNN), named Adaptive Force-Environment Estimator (WNN-AFEE). Unlike disturbance observers, WNN_AFEE does not require the inverse of the Jacobian transpose for computing the force, thus, it has no computational problem near singular points. In this scheme, WNN estimates the external force disturbance to attenuate its effects on the control system performance by estimating the environment model. A Lyapunov based design is presented to determine adaptive laws for tuning WNN parameters. Another advantage of the proposed approach is that it can estimate the force even when there are some parametric uncertainties in the robot model, because an additional adaptive law is designed to estimate the robot parameters. In a theorem, the stability of the closed loop system is proved and a general condition is presented for identifying the force and robot parameters. Some suggestions are provided for improving the estimation and control performance. Then, a WNN-AFEE is designed for a planar manipulator as an example, and some simulations are performed for different conditions. WNN_AFEE results are compared attentively with the results of an adaptive force estimator and a disturbance estimator. These comparisons show the efficiency of the proposed controller in dealing with different conditions.     

Adaptive–interpolative binarization with stroke preservation for restoration of faint characters in degraded documents

A novel technique for binarization with stroke preservation of faint characters in degraded documents is proposed. It works in a multi-scale framework with an adaptive–interpolative thresholding technique. Instead of computing a global threshold value, it computes the local threshold values for a small set of grid points by observing the intensity pattern of the pixels lying in the concerned grid cells. Estimated thresholds are used, in turn, to compute the threshold values of all the remaining pixels using a fast-yet-efficient interpolation procedure. To handle noises in degraded images, this grid-based adaptive thresholding is applied in successively reducing scales to obtain the near-optimal binarization as a set of connected components. After a post-processing meant for stroke preservation with these connected components, we get the final output. Exhaustive experimentation and comparison with other existing methods have been successfully carried out with benchmark datasets and also with our own datasets.     

Adaptive neuro-fuzzy prediction of grasping object weight for passively compliant gripper

The development of universal grippers able to pick up unfamiliar objects of widely varying shapes and surfaces is a very challenging task. Passively compliant underactuated mechanisms are one way to obtain the gripper which could accommodate to any irregular and sensitive grasping objects. The purpose of the underactuation is to use the power of one actuator to drive the open and close motion of the gripper. The fully compliant mechanism has multiple degrees of freedom and can be considered as an underactuated mechanism. This paper presents a new design of the adaptive underactuated compliant gripper with distributed compliance. The optimal topology of the gripper structure was obtained by iterative finite element method (FEM) optimization procedure. The main points of this paper are in explanation of a new sensing capability of the gripper for grasping and lifting up the gripping objects. Since the sensor stress depends on weight of the grasping object it is appropriate to establish a prediction model for estimation of the grasping object weight in relation to sensor stress. A soft computing based prediction model was developed. In this study an adaptive neuro-fuzzy inference system (ANFIS) was used as soft computing methodology to conduct prediction of the grasping objects weight. The training and checking data for the ANFIS network were obtained by FEM simulations.     

自适应大流量安全阀的流固耦合分析与保压实验

为提高自适应大流量安全阀关键零件的可靠性及寿命,利用UG软件建立自适应大流量安全阀关键零件的三维模型,并借助ANSYS Fluent软件对其进行了网格划分,通过单向流固耦合分析得到了一级锥阀、二级差动阀芯等关键零件的应力、应变云图;为进一步研究自适应大流量安全阀的低压密封性,利用ZF-2WG液压支架阀综合实验台对其进行了6、14 MPa 2种不同压力的打压实验。仿真及实验结果表明：一级锥阀的锥面附近区域为应力集中区域,锥尖附近区域为应变集中区域;二级阀芯4个阻尼孔靠差动腔侧的出口处为应力集中区域,二级阀芯外环形差动腔接触流体区域为应变集中区域;通过操作控制P口压力为6、14 MPa,保压时间为120 s,压力值基本保持在设定值,保压效果非常理想。     

轮式移动机器人滑移轨迹跟踪控制策略研究

针对轮式移动机器人在滑移条件下的轨迹跟踪问题,提出一种自适应模糊控制策略。利用模糊状态观测器对未知的复杂系统模型进行速度估计和补偿,通过设计输出向量将位置约束转换为输出约束,并构造Barrier Lyapunov函数来保证机器人的运动约束,在此基础上设计更简单的纵向滑移模型,利用李亚普诺夫定理分析闭环系统的稳定性,证明了闭环系统中所有信号都是有界的。最后通过仿真和实验验证了自适应模糊控制策略在轮式机器人纵向滑移情况下的有效性和实用性。     

基于ANFIS?P ID的四旋翼姿态控制系统设计与仿真

四旋翼飞行器在飞行控制系统非常复杂,在飞行中极容易受到外界因素的影响而改变飞行姿态, 为保证飞行器的姿态能实现自适应平衡,系统结合飞行器时变动力学模型,设计了一种自适应神经模糊推理系统（Adaptive Neuro Fuzzy Inference System,ANFIS)的PID控制方法,该方法具有自动检测、处理、执行的能力,同时能够有效地降低飞行中出现的卡顿、震荡等现象。通过采集数据在Matlab/Simulink中仿真,同时人为增加一些常见的干扰因素,观察各控制通道的参数变化曲线对自适应控制系统对飞行姿态做出实时有效地调整,确保飞行器在飞行姿态控制中能够很好地保持稳定性和鲁棒性。     

“水城”计划：柏林城市滨水地带的复兴

城市滨水地带曾经在工业的发展中发挥过巨大的作用。进入后工业社会以来，随着经济社会形态和产业结构的变化，城市中的滨水工业生产用地以及仓储用地相继被废弃。这些已经被污染的用地尽管需要花费高昂的代价去整治，但也具有很高的商业开发价值。本文介绍了德国统一之后柏林城市滨水地带再开发的两个大型项目实例，以期为国内类似问题和项目的研究提供借鉴和参考。     

SOLVING AN URBAN RIVER EROSION PROBLEM ON THE TILMORE BROOK, HAMPSHIRE (UK)

The Tlimore Brook, In Hampshire, typifies the Impact of new housing development that has taken place In phases over the past 20 years or so, on a river corridor. However, the issue is not one of flooding, because the channel itself had been straightened and deepened in historical times and had been adjusted further by down-cutting; thereby forming an over-large channel sufficient to contain flood flows. Perhaps rarely for lowland Britain, the key problem was that of erosion, threatening adjacent properties. This paper describes the nature of the erosion problem and the subsequent geomorphological design to mitigate it. A key unique feature of this project was the extent of backfilling required, over the entire length, to raise the over-deep channel bed. The project was constructed in 2003.