Robust adaptive control of underactuated ships on a linear course with comfort

This paper addresses an important problem in ship control application—the robust stabilization of underactuated ships on a linear course with comfort. Specifically, we develop a multivariable controller to stabilize ocean surface ships without a sway actuator on a linear course and to reduce roll and pitch simultaneously. The controller adapts to unknown parameters of the ship and constant environmental disturbances induced by wave, ocean current and wind. It is also robust to time-varying environmental disturbances, time-varying change in ship parameters and other motions of the ship such as surge and heave. The roll and pitch can be made arbitrarily small while the heading angle and sway are kept to be in reasonably small bounds. The controller development is based on Lyapunov’s direct method and backstepping technique. A Lipschitz continuous projection algorithm is used to update the estimate of the unknown parameters to avoid the parameters’ drift due to time-varying environmental disturbances. Simulations on a full-scale catamaran illustrate the effectiveness of our proposed controller.     

Some Results on the Spatial Breakdown Point of Robust Point Estimates of the Variogram

The effect of outliers on estimates of the variogram depends on how they are distributed in space. The ‘spatial breakdown point’ is the largest proportion of observations which can be drawn from some arbitrary contaminating process without destroying a robust variogram estimator, when they are arranged in the most damaging spatial pattern. A numerical method is presented to find the spatial breakdown point for any sample array in two dimensions or more. It is shown by means of some examples that such a numerical approach is needed to determine the spatial breakdown point for two or more dimensions, even on a regular square sample grid, since previous conjectures about the spatial breakdown point in two dimensions do not hold. The ‘average spatial breakdown point’ has been used as a basis for practical guidelines on the intensity of contaminating processes that can be tolerated by robust variogram estimators. It is the largest proportion of contaminating observations in a data set such that the breakdown point of the variance estimator used to obtain point estimates of the variogram is not exceeded by the expected proportion of contaminated pairs of observations over any lag. In this paper the behaviour of the average spatial breakdown point is investigated for cases where the contaminating process is spatially dependent. It is shown that in two dimensions the average spatial breakdown point is 0.25. Finally, the ‘empirical spatial breakdown point’, a tool for the exploratory analysis of spatial data thought to contain outliers, is introduced and demonstrated using data on metal content in the soils of Sheffield, England. The empirical spatial breakdown point of a particular data set can be used to indicate whether the distribution of possible contaminants is likely to undermine a robust variogram estimator.     

杠杆点评估及设计空间抗差

本分析了杠杆点的几何含义和统计特征,从杠杆点的保差性,矩阵的摄动和参数估值可靠性的观点出发讨论了杠杆点的不利和有利的两个方面,提出了一个全面的设计空间抗差方案。     

成都城市发展对热岛强度影响的主成份回归分析

本文对成都市总人口、建成区面积等11个因子、作了主成份回归L-S估计和M-估计,讨论了成都城市发展对“热岛”强度的主要影响因子。结果表明,城区房屋建筑面积及总人口数是影响城市气候(气温)的主要因子,其次为城市人口总户数、建成面积等。 文中,对回归方程进行了拟合计算,回归效果比较满意(尤其是稳健回归)。     

Discrete time-delay control of an autonomous underwater vehicle: Theory and experimental results

A discrete time-delay control (DTDC) law for a general six degrees of freedom unsymmetric autonomous underwater vehicle (AUV) is presented. Hydrodynamic parameters like added mass coefficients and drag coefficients, which are generally uncertain, are not required by the controller. This control law cancels the uncertainties in the AUV dynamics by direct estimation of the uncertainties using time-delay estimation technique. The discrete-time version of the time-delay control does not require the derivative of the system state to be measured or estimated, which is required by the continuous-time version of the controller. This particularly provides an advantage over continuous-time controller in terms of computational effort or availability of sensors for measuring state derivatives, i.e., linear and angular accelerations. Implementation issues for practical realization of the controller are discussed. Experiments on a test-bed AUV were conducted in depth, pitch, and yaw degrees of freedom. Results show that the proposed control law performs well in the presence of uncertainties.     

On the use of iterative re-weighting least-squares and outlier detection for empirically modelling rates of vertical displacement

The proper identification and removal of outliers in the combination of rates of vertical displacements derived from GPS, tide gauges/satellite altimetry, and GRACE observations is presented. Outlier detection is a necessary pre-screening procedure in order to ensure reliable estimates of stochastic properties of the observations in the combined least-squares adjustment (via rescaling of covariance matrices) and to ensure that the final vertical motion model is not corrupted and/or distorted by erroneous data. Results from this study indicate that typical data snooping methods are inadequate in dealing with these heterogeneous data sets and their stochastic properties. Using simulated vertical displacement rates, it is demonstrated that a large variety of outliers (random scattered and adjacent, as well as jointly influential) can be dealt with if an iterative re-weighting least-squares adjustment is combined with a robust median estimator. Moreover, robust estimators are efficient in areas weakly constrained by the data, where even high quality observations may appear to be erroneous if their estimates are largely influenced by outliers. Four combined models for the vertical motion in the region of the Great Lakes are presented. The computed vertical displacements vary between  − 2 mm/year (subsidence) along the southern shores and 3 mm/year (uplift) along the northern shores. The derived models provide reliable empirical constraints and error bounds for postglacial rebound models in the region.     

测量平差模型的抗差最小二乘解及影响函数

抗差Ｍ估计是使用最广泛、计算较简明的抗差估计法。基于多维Ｍ估计原理，本文建立了经典测量平差函数模型的抗差解，并推导出相应的误差影响函数；为了使抗差估计适于不同类型以及不同先验精度的各类观测值的混合平差，将使用等价权原理构造抗差最小二乘解式。     

Robust估计的算法优化

本文分析了Ｒｏｂｕｓｔ估计收敛慢的原因，提出以最小二乘平差的残差（Ｖ）为初始信息，用Ｌ１估计的权函数所计算的权力初始权，根据迭代计算的残差的大小，及残差的变化所提供的信息，构造出加速收敛的算法，计算结果表明，较之一般的方法，迭代次数显著减少，辨识杠杆点含粗差的能力有较大提高，即搜索粗差的效率有很大提高。     

自适应Lp估计及其在SLR数据预处理中的应用

本文简要介绍了自适应Ｌｐ估计的有关理论和求解方法，并对ＳＬＲ数据的测量误差作了统计分析。发现ＳＬＲ数据的测量误差服从ｐ值不定的ｐ范分布。本文ＳＬＲ数据预处理实例表明自适应Ｌｐ估计能给出比ＬＳ估计更为稳健有效的拟合参数。当观测值粗差高达６６％时，自适应Ｌｐ估计仍能给出可靠的拟合参数，效果明显优于传统的ＬＳ估计。