Singular perturbation of strictly positive realness

The robustness of the strictly positive real (SPR) condition of linear time-invariant multi-input, multi-output (LTI-MIMO) singularly perturbed systems is examined. A necessary and sufficient condition under which the full system is SPR, is proved. This robustness result is an extension of the analysis for the Popov-Kalman-Yakubovich lemma by V.R. Saksena and P.V. Kokotovic [7].     

Model reference adaptive control of air-lubricated capstan drive for precision positioning

Because friction-induced nonlinearities in positioning systems are generally range of motion-dependent, dual-model or dual-stage strategies are often adopted to deal with the inconsistencies encountered when a system moves from submicrometer steps (micro mode) to larger scale strokes (macro mode). Although good performance is usually obtained when each model/stage operates in its designed range of motion, a system frequently performs less satisfactorally when operating near the switching point between models or stages. An air-lubricated capstan drive was used in this study to minimize the discrepancy between macro and micro modes, and a single-mode MRAC was developed to control the capstan drive system for precision positioning. Accuracy better than ±15 nm with no overshooting was achieved in all conditions tested (including 50 nm, 500 nm and 10 μm steps). Disturbance resistance of the system also proved to be satisfactory.     

A pole-assignment algorithm for linear state feedback

A new algorithm for the pole-assignment problem of a controllable time-invariant linear multivariable system with linear state feedback is presented. The resulting feedback matrix is a least-squares solution and is robust in a loose sense. The method is based on the controllability canonical (staircase) form and amounts to a new proof for the existence of a solution of the pole-assignment problem. Illustrative examples are given.     

一类关于鲁棒性和敏感性的泛函的优化

本文给出了一类泛函的优化方法.这类泛函包括反映系统鲁棒性和敏感性的目标函数. 其优化是通过-Rm×n→Rm×n的映射来实现的.该映射将所有配置系统极点的反馈矩阵参数 化为一自由矩阵变量的函数.     

Robustness in organizational-learning oriented classifier system

 An organizational-learning oriented classifier system (OCS) is an extension of learning classifier systems (LCSs) to multiagent environments, where the system introduces the concepts of organizational learning (OL) in organization and management science. To investigate the capabilities of OCS as a new multiagent-based LCS architecture, this paper specifically focuses on the robustness of OCS in multiagent environments and explores its capability in space shuttle crew task scheduling as one of real-world applications. Intensive simulations on a complex domain problem revealed that OCS has robustness capability in the given problem. Concretely, we found that OCS derives the following implications on robustness: (1) OCS finds good solutions at small computational costs even after anomaly situations occur; and (2) this advantage becomes stronger as the number of anomalies increases.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

基于扩张状态观测器的直线倒立摆状态反馈控制研究

针对直线倒立摆的控制问题,利用拉格朗日方法对实际物理模型进行线性化处理建立数学模型,为了提高控制精度,将不确定外扰和未建模动态视为一个综合扰动项,运用扩张状态观测器对系统状态和综合扰动项进行观测,设计了基于扩张状态观测器的直线倒立摆状态反馈稳摆控制器;用能量反馈方法和bang-bang控制器实现倒立摆起摆到稳摆的切换。通过无干扰和有干扰状态直线倒立摆起摆到稳摆过程的实验研究,表明系统能够有效的抑制外界干扰,具有较强的鲁棒性。     

Augmenting security of biometric with watermarking

This paper presents a new blind biometric watermarking scheme based on discrete wavelet transform for biometric template protection. We are using fingerprint feature and iris feature as multiple watermarks instead of randomly generated Gaussian noise type watermark. Watermark embedding locations are selected by measuring power level of each coefficient which gives sensibility of human eye to local image perturbations. Though biometric features are embedded sequentially, care is taken that most significant features are embedded to those locations whose power level is maximum which provides more robustness. We embed watermark into mid-frequency sub-band by modifying the amplitude of selected coefficient based on comparison between original and estimated values. Estimated value of coefficient is calculated from average sub-band of the same resolution level of the cover image. A reliable watermark extraction scheme is developed for the extraction of watermark from distorted image. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks. We show that the proposed scheme also gives adjustability to the user for selecting P percentage of retained wavelet coefficients.     

数控插齿机热误差模块化稳健性预测模型建立

针对数控插齿机固有的主轴进给系统结构带来的传动间隙引起波动性热变形建模预测精度不高的问题,提出一种基于均值平滑处理波动的模块化建模方法。利用模糊聚类结合灰色关联度方法和多元线性回归对该机床主轴x、y向分别建立热误差补偿模型,并计算预测残余值在不同分布范围的概率。结果表明：与传统热误差建模方法相比,模块化预测残余值在不同范围的分布较均匀,稳健性得到了有效提升,为热误差模块化建模方法提供了参考。     

数控机床交流伺服系统的复合控制研究

针对常规P-P与PPI控制存在的问题，提出了在数控机床交流伺服系统中，采用带速度和加速度作为前馈控制，模糊自校正PID控制作为位置反馈控制的复合控制器，实验证明可以显著提高控制系统的控制精度，大大降低跟踪误差，具有较强的鲁棒性。