Model-free adaptive control method with variable forgetting factor for unmanned surface vehicle control

We present a new type of model-free adaptive control (MFAC) method based on an adaptive forgetting factor for unmanned surface vehicle (USV) heading control under uncertain influence. Firstly, we analyze the compact form dynamic linearization based MFAC (CFDL-MFAC) method and its main problems with regard to USV heading control. Secondly, in order to address the problems of overshoot, oscillation, and slow convergence of the heading control with the MFAC method and considering the dynamics of the USV heading control subsystem, we introduce an adaptive forgetting factor into the CFDL-MFAC to arrive at the CFDL-MFAC with variable forgetting factor (CFDL-MFAC-VFF) method. Our simulation studies show that the CFDL-MFAC-VFF method yields low overshoot and low oscillations and is insensitive to changes in the system parameters and output error. Finally, our field experiments with the small USV “Dolphin-I” demonstrate the effectiveness and engineering practicability of our proposed method.     

一种分析台风路径预报误差的新方法

台风路径预报误差应包括距离误差和方向误差两个方面,而在以往的业务应用和科学研究中偏向于只考虑对应时刻预报和观测位置点间的距离误差。本文对评估台风路径误差的方法进行了改进,在距离误差基础上建立了一种新的表征台风路径误差的方法——多因子误差法。本文以中国气象局整编的热带气旋最佳路径数据为标准,对2008和2009年中国气象局、美国台风联合预警中心和日本气象厅预报的西北太平洋热带气旋路径,采用新的表征热带气旋路径预报误差的多因子误差法进行分析,并与普遍采用的距离误差法进行对比,结果表明:多因子误差分析方法和距离误差分析方法存在比较明显的差异,多因子误差法优势比较明显。本文是对更科学的台风路径预报误差评定方法的有益探索,有一定的参考价值。     

基于次季节—季节(S2S)模式的中国东部夏季日降水预报评估

为理解次季节—季节(subseasonal to seasonal,S2S)模式的预报技巧,利用台站降水观测资料对中国气象局(China Meteorological Administration,CMA)、欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)模式公共回报期1999—2010 年108°E 以东的中国大陆东部夏季日降水及极端降水预报展开评估。结果表明,ECMWF 预报整体表现最佳、NCEP 次之、CMA 相对较弱,各模式随预报时间的增长均呈现当观测偏湿(干)时预报倾向偏干(湿)的特点,在 S2S 时间尺度基本丧失预报技巧,具有很大的改进空间。极端降水临界阈值的界定方法会直接影响单个台站的评估结果,但对区域整体预报技巧影响不大。S2S 模式预报的均方根误差在观测降水量越多时往往越大;预报值与观测值的相关系数在所有(极端)降水事件中呈连续(振荡)衰减,甚至出现负相关;均方技巧评分在所研究降水事件较多的情况下表现更好。各模式在所有降水事件中的空报率要远高于漏报率,但在极端降水事件中恰好相反。降水预报检验指标在绝对极端降水分级检验中的表现逐级变差,各模式预报中基本不出现特大暴雨,CMA 对极端降水事件发生的预报准确率较低。     

基于分段自适应算法的浅海水深遥感反演融合模型研究

对于水深光学遥感反演研究，虽然已经建立了大量的模型方法，然而对于不同水深段，同一模型的反演精度各异，且采用单一模型进行水深反演得到的整体反演精度未必最佳。为了提高水深光学遥感反演的整体精度，本文提出一种分段自适应水深反演融合模型，模型在误差估计的基础上，结合了对数线性模型、对数转换比值模型、改进的对数转换比值模型与多调节因子模型的优势。利用模型在西沙群岛东岛开展了水深遥感反演实验，从整体反演精度、不同水深段反演精度及逐米水深精度等角度进行分析，结果表明，分段自适应融合模型的整体精度最高，平均绝对误差为1.09 m，平均相对误差达到16.06%；分水深段来看，分段自适应融合模型在多数不同水深段内的反演效果均最好；从逐米精度来看，分段自适应融合模型在大部分逐米水深段的反演能力均优于其他模型。     

Low complexity adaptive equalizers for underwater acoustic communications

Interference signals due to scattering from surface and reflecting from bottom is one of the most important problems of reliable communications in shallow water channels. To solve this problem, one of the best suggested ways is to use adaptive equalizers. Convergence rate and misadjustment error in adaptive algorithms play important roles in adaptive equalizer performance. In this paper, affine projection algorithm （APA）, selective regressor APA（SR-APA）, family of selective partial update （SPU） algorithms, family of set-membership （SM） algorithms and selective partial update selective regressor APA （SPU-SR-APA） are compared with conventional algorithms such as the least mean square （LMS） in underwater acoustic communications. We apply experimental data from the Strait of Hormuz for demonstrating the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error （MSE） of SR-APA, SPU-APA0 SPU-normalized least mean square （SPU-NLMS）, SPU-SR-APA0 SM-APA and SM-NLMS algorithms decrease in comparison with the LMS algorithm. Also these algorithms have better convergence rates than LMS type algorithm.     

Spatial diversity equalization applied to underwater communications

Underwater acoustic digital communication is difficult because of the nature of the fading multipath channels. Digital signal processing, such as adaptive equalization, is known to greatly improve the communication data rate by limiting intersymbol interference (ISI). However, existing underwater acoustic equalization studies are limited to single-channel techniques, and spatial diversity processing is limited to selection or combining. In this paper, we design minimum mean-square error (MMSE) equalizers jointly among all spatial diversity channels. We call this spatial diversity equalization (SDE). Results are based on a very sparse vertical array in a midrange underwater acoustic channel. We study the effect of element number and placement, the length of the equalization filters, and linear feedforward versus nonlinear decision feedback algorithms. A suboptimum equalizer combiner (EC) is studied to alleviate the computational intensity of JCE. We first design the system for a known acoustic channel; later, some results are verified using adaptive algorithms. Results are presented both in terms of the mean-square error (MSE) and the probability of a symbol error. The latter is important as it is the ultimate interest for a digital communication system. We found that system performance improves rapidly with an increase in the number of spatial channels     

中美两套西北太平洋热带气旋资料集的差异分析

利用中国气象局(CMA)和美国联合台风预警中心(JTWC)两套西北太平洋热带气旋(TC)资料集,对比分析了两者在1951—2005年TC定位和定强方面的差异。结果表明:两套资料定位差在20世纪50年代至60年代初及1988年至90年代差异较大;地理分布上主要是在TC登陆后所在的地区及高纬度洋面上差别较大。定强方面,CMA资料在20世纪50年代及60年代末至70年代初TC强度明显大于JTWC资料,JTWC资料则在80年代末以后的时段TC强度显著大于CMA资料;地理分布上定强差大的区域在80年代以前分布较零散,之后随着JTWC资料定强增大,其在西北太平洋洋面上强度显著偏强,CMA资料同期则在亚洲大陆沿岸部分地区强度较强。进一步分析显示,两套资料集之间的差异和TC观测技术的变化之间存在密切关系。在气象卫星使用以前(1951年至60年代初),以及美国空军飞机观测终止之后(1988年以后),两者无论是在定位还是定强上都存在很大差异;而两者定强差最小的时期(1973—1987年)则正好对应了飞机观测和Dvorak技术在TC观测上同时被使用的时段。两套西北太平洋TC资料集总体差异明显,却又各具特点,目前很难判断哪一套资料集更加可靠。但对于影响中国TC,CMA资料集具有明显优势。     

An adaptive-hybrid algorithm for geoacoustic inversion

This paper presents an adaptive hybrid algorithm to invert ocean acoustic field measurements for seabed geoacoustic parameters. The inversion combines a global search (simulated annealing) and a local method (downhill simplex), employing an adaptive approach to control the trade off between random variation and gradient-based information in the inversion. The result is an efficient and effective algorithm that successfully navigates challenging parameter spaces including large numbers of local minima, strongly correlated parameters, and a wide range of parameter sensitivities. The algorithm is applied to a set of benchmark test cases, which includes inversion of simulated measurements with and without noise, and cases where the model parameterization is known and where the parameterization most be determined as part of the inversion. For accurate data, the adaptive inversion often produces a model with a Bartlett mismatch lower than the numerical error of the propagation model used to compute the replica fields. For noisy synthetic data, the inversion produces a model with a mismatch that is lower than that for the true parameters. Comparison with previous inversions indicates that the adaptive hybrid method provides the best results to date for the benchmark cases     

在Zebiak-Cane模式中观测MJO强迫对ENSO可预报性的影响, 第1部分:对最大预报误差的影响

With the observational wind data and the Zebiak-Cane model, the impact of Madden-Julian Oscillation (MJO) as external forcing on El Ni(n)o–Southern Oscillation (ENSO) predictability is studied. The obs...     

新型抗脑缺血海洋新药989对血栓性大鼠脑缺血的保护作用

该文采用 Fe Cl3局部涂抹损伤血管造成的大鼠大脑中动脉血栓模型 ,以脑梗塞范围、行为障碍、脑组织病理改变为观察指标 ,研究 989对脑血栓所致局部缺血性脑损伤的保护作用。结果表明 :9895.0、10 .0 mg/ kg手术后 30 min舌下静脉注射能明显缩小脑栓塞大鼠 2 4 h后的脑梗塞范围 ;98910 .0 mg/ kg能明显改善脑栓塞大鼠的行为障碍。脑组织病理检查发现 ;98910 .0 mg/ kg组动物大脑中动脉内血栓形成极少或未形成 ,脑组织缺血病变较轻。表明 989对栓塞性脑损伤具有明显的保护作用     

On the Use of Adaptive/Integral Actions for Six-Degrees-of-Freedom Control of Autonomous Underwater Vehicles

In this paper, the control of autonomous underwater vehicles (AUVs) in six-degrees-of-freedom (6-DOFs) is analyzed in a comparison study among several controllers. At steady state, the vehicle needs to compensate for two dynamic effects, the ocean current and the restoring forces; the appropriateness of the adaptive/integral action designed with respect to the persistent effects is discussed. Moreover, for each controller, an adaptive/integral proportional derivative (PD) plus gravity compensation-like version is derived and eventually modified so as to achieve null steady-state error under modeling uncertainty and presence of ocean current. Numerical simulations are presented to better illustrate the controllers' behavior.     

Spatially and temporally varying adaptive covariance inflation for ensemble filters

Ensemble filters are used in many data assimilation applications in geophysics. Basic implementations of ensemble filters are trivial but are susceptible to errors from many sources. Model error, sampling error and fundamental inconsistencies between the filter assumptions and reality combine to produce assimilations that are suboptimal or suffer from filter divergence. Several auxiliary algorithms have been developed to help filters tolerate these errors. For instance, covariance inflation combats the tendency of ensembles to have insufficient variance by increasing the variance during the assimilation. The amount of inflation is usually determined by trial and error. It is possible, however, to design Bayesian algorithms that determine the inflation adaptively. A spatially and temporally varying adaptive inflation algorithm is described. A normally distributed inflation random variable is associated with each element of the model state vector. Adaptive inflation is demonstrated in two low-order model experiments. In the first, the dominant error source is small ensemble sampling error. In the second, the model error is dominant. The adaptive inflation assimilations have better mean and variance estimates than other inflation methods.     

基于双注意力机制的台风轨迹预测模型

台风轨迹的准确预测对于减少台风灾害及风险评估意义重大。本文提出了一种基于双注意力机制的台风轨迹预测模型(Dual-Attention-Encoder-Decoder),首先根据台风轨迹数据计算台风轨迹的变化曲率,将台风曲率序列与台风轨迹序列一同作为预测模型的特征输入,充分考虑了台风轨迹中隐藏的转向、偏折信息;然后构建双注意力机制增强的编码器-解码器网络(Encoder-Decoder)作为预测模型,利用特征注意力机制和时间注意力机制分别对模型输入和隐藏状态进行权重分配,能够学习输入特征和预测目标之间的关系,并且有效解决编码器-解码器结构对过长序列预测的性能下降问题,编码器和解码器均采用LSTM网络,能够存储长时间依赖并且收敛性好,不易发生梯度消失或爆炸;最后,本文使用1949—2017年中国气象局提供的西北太平洋台风最佳路径数据集,将DA-Encoder-Decoder模型与BP、SVR、LSTM、ELM等模型进行对比,分别对24 h、48 h、72 h台风轨迹进行预测。结果表明:DA-Encoder-Decoder模型的均方根误差和实际误差距离指标均优于其他四种预测方法,验证了本文方法的有效性。     

北极冰下水声通信中改进的最小均方/四次方直接自适应均衡器

本文提出了一种适用于北极冰下水声通信的最小均方/四次方直接自适应均衡器（LMS/F-DAE）。它能处理基带复信号,与LMS相比,具有更好的均衡效果。考虑到均衡器的稀疏特性,在其代价函数中加入自适应范数（AN）作为约束。它能根据均衡器系数的大小自适应变化：对于小系数,此约束项存在以加快收敛速度;对于大系数,此约束项不存在以减小均衡误差。利用第九次中国北极科学考察得到的实验数据验证AN-LMS/F-DAE的性能。结果表明,与传统的LMS/F-DAE相比,AN-LMS/F-DAE能提升均衡器的稀疏性且均衡性能更优。     

CSI feedback-based CS for underwater acoustic adaptive modulation OFDM system with channel prediction

In this paper, we investigate the performance of adaptive modulation （AM） orthogonal frequency division multiplexing （OFDM） system in underwater acoustic （UWA） communications. The aim is to solve the problem of large feedback overhead for channel state information （CSI） in every subcarrier. A novel CSI feedback scheme is proposed based on the theory of compressed sensing （CS）. We propose a feedback from the receiver that only feedback the sparse channel parameters. Additionally, prediction of the channel state is proposed every several symbols to realize the AM in practice. We describe a linear channel prediction algorithm which is used in adaptive transmission. This system has been tested in the real underwater acoustic channel. The linear channel prediction makes the AM transmission techniques more feasible for acoustic channel communications. The simulation and experiment show that significant improvements can be obtained both in bit error rate （BER） and throughput in the AM scheme compared with the fixed Quadrature Phase Shift Keying （QPSK） modulation scheme. Moreover, the performance with standard CS outperforms the Discrete Cosine Transform （DCT） method.     

基于无记忆状态观测器的多时滞不确定非线性系统的自适应控制

针对一类多时滞不确定非线性系统,研究了基于无记忆状态观测器的自适应控制问题.时滞状态扰动的上界未知,在控制中通过自适应律估计未知参数,并利用估计值设计了不依赖于时滞的无记忆状态观测器和控制器,基于Lyapunov-Krasovskii函数证明了观测误差渐近收敛到零.最后仿真结果说明了该方法的有效性.     

不同保存时间下叶绿素a标样对响应因子的影响

利用叶绿素a色素标样对高效液相色谱(HPLC)系统进行校正,主要研究叶绿素a标样在不同的保存时间下对响应因子的影响,结果表明,随着保存时间的延长,标样的纯度有很大的变化,同时响应因子也有较大的变化,当得到的响应因子最小时,引起的相对偏差最大,为50.29%。     

Study of Seabed Pullout Resistance on a Quadrate Foundation Using Adaptive Time-Stepping Method

We developed a solid-fluid analysis procedure that can simulate the seabed pullout resistance based on two adaptive time-stepping methods. One is heuristic time stepping, and the other is based on the truncation error estimation in temporal discretization. The pullout resistance is investigated through experiments and numerical simulations. The results show that the proposed adaptive stepping methods can deal with the un-convergence problems caused by the time increment and can improve the calculation efficiency. The base suction, related to the area of the negative pore water pressure, is generated under the structure and provides the pullout resistance.     

Signal recovery in a reverberation-limited environment

The problem of recovering signals masked by reverberation is considered. Reverberation data from a shallow-water active sonar experiment in conjunction with simulated echoes are used to examine the potential for signal recovery offered by adaptive filtering and prediction. The deterministic least squares lattice filter is the central adaptive estimator of choice. The prediction error lattice is used to selectively "whiten" the composite process by controlling the algorithm adaptation speed. This is shown to result in significant signal enhancement for low-Doppler echoes masked by reverberation. Adaptive noise canceling with multiple reference beams is shown to be successful in extracting even zero-Doppler echoes from the reverberation background.     

Linear genetic programming for prediction of circular pile scour

Genetic programming (GP) has nowadays attracted the attention of researchers in the prediction of hydraulic data. This study presents linear genetic programming (LGP), which is an extension to GP, as an alternative tool in the prediction of scour depth around a circular pile due to waves in medium dense silt and sand bed. Field measurements were used to develop LGP models. The proposed LGP models were compared with adaptive neuro-fuzzy inference system (ANFIS) model results. The predictions of LGP models were observed to be in good agreement with measured data, and quite better than ANFIS and regression-based equation of scour depth at circular piles. The results were tabulated in terms of statistical error measures and illustrated via scatter plots.