模糊C-球壳聚类算法及其在血液细胞图像中的应用

文章从经典的模糊C均值算法开始通过改变其中相似性的度量形式，介绍了一种模糊C球壳聚类（FCSS）算法。在将该算法应用于细胞显微图像半径统计时，采用基于形态学的图像预处理措施，可以获得FCSS算法中有关原型模式的知识，加快收敛速度并避免随机初始化造成的局部极小问题。     

空间机器人姿态与末端抓手协调运动的鲁棒自适应控制

本文讨论了载体姿态受控、位置不受控制的漂浮基空间机器人协调运动的控制问题。借助于虚拟扩展系统的输入与输出,得到了一组关于惯性参数呈线性函数关系的系统控制方程。以此为基础,针对空间机器人系统中不确定参数与未知参数并存的复杂情况,设计了载体姿态与末端抓手惯性空间轨迹协调运动的鲁棒自适应控制方案。利用两杆空间机器人系统进行了系统仿真运算,仿真结果证实了上述控制方案的有效性。由于对系统待估计参数作了分类,并充分利用系统信息对系统不确定参数采用保持鲁棒性而不是在线估计的方法,提到的控制方案具有计算量小的优点,有助于缓解机载计算机运算能力有限的矛盾。     

Generation of adaptive gait patterns for quadruped robot with CPG network including motor dynamic model

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environments. The CPGs act as the flexible oscillators of the joints and adjust joint angles to required values. The CPGs are interconnected with each other and sets of their coupling parameters are adjusted by a genetic algorithm so that the quadruped robot can realize stable and adequate gait patterns. Generation of gait patterns results in the formation of the CPG networks suitable for the formation of not only a straight walking pattern but also of rotating gait patterns. Experimental results demonstrate that the proposed CPG networks are effective for the automatic adjustment of the adaptive gait patterns for the tested quadruped robot under various environments. Furthermore, the target tracking control based on image processing is achieved by combining the general gait patterns. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(1): 35–43, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20225     

Minimum switching control for adaptive tracking

The switching adaptive control method has been used for quite a few years to solve the adaptive stabilization and model reference adaptive control problems. However, a serious problem with the switching control method is that the number of ‘candidate’ controllers can potentially be very large, especially for multi‐input–multi‐output systems. In this paper, we consider a class of minimum‐phase multi‐input–multi‐output plants with some mild compactness assumptions. Given any polynomial reference input, we provide a switching control law which guarantees exponentially stability of the closed‐loop system with exponential tracking performance. The main contribution of the paper is that we give the minimum number of candidate controllers required for switching. In particular, the number is equal to 2 for single‐input–single‐output plants (one for each sign of the high‐frequency gain), and is equal to 2^m for m‐input–m‐output plants. That is, the number is independent of the degree and the relative degree of the plant. Copyright © 2006 John Wiley & Sons, Ltd.     

Dynamical adaptive synchronization

The notions of dynamical synchronization and adaptive dynamical synchronization problems are introduced. The algorithm solving adaptive synchronization problem for a subclass of Lurie systems with exciting input is proposed. The performance and potentialities of proposed solutions are demonstrated by two examples related to formation control and self‐organization of swarm systems. Copyright © 2006 John Wiley & Sons, Ltd.     

A novel robust current control approach using adaptive line enhancer for three‐phase current‐source active power filter

An effective system control method is presented for applying a three‐phase current‐source PWM converter with a deadbeat controller to active power filters (APFs). In the shunt‐type configuration, the APF is controlled such that the current drawn by the APF from the utility is equal to the current harmonics and reactive current required for the load. To attain the time‐optimal response of the APF supply current, a two‐dimensional deadbeat control scheme is applied to APF current control. Furthermore, in order to cancel both the delay in the two‐dimensional deadbeat control scheme and the delay in DSP control strategy, an Adaptive Line Enhancer (ALE) is introduced in order to predict the desired value three sampling periods ahead. ALE has another function of bringing robustness to the deadbeat control system. Due to the ALE, settling time is made short in a transient state. On the other hand, total harmonic distortion (THD) of source currents can be minimized compared to the case where ideal identification of the controlled system can be made. The experimental results obtained from the DSP‐based APF are also reported. The compensating ability of this APF is very high in accuracy and responsiveness although the modulation frequency is rather low. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 50–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20014     

A Unified View on Clustering Binary Data

Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This paper studies the problem of clustering binary data. Binary data have been occupying a special place in the domain of data analysis. A unified view of binary data clustering is presented by examining the connections among various clustering criteria. Experimental studies are conducted to empirically verify the relationships.     

MIMO系统的自适应均衡技术研究

研究了用于MIMO系统的自适应均衡的几种算法，比较了最小均方算法(LMS)、递归最小二乘算法(RLS)、判决反馈算法(DFE)、格型梯度自适应均衡算法(GALE)和格型最小二乘自适应均衡算法(LSALE)。文章的最后给出了仿真结果及结论。     

An adaptive non‐conforming finite‐element method for Reissner–Mindlin plates

Adaptive algorithms are important tools for efficient finite‐element mesh design. In this paper, an error controlled adaptive mesh‐refining algorithm is proposed for a non‐conforming low‐order finite‐element method for the Reissner–Mindlin plate model. The algorithm is controlled by a reliable and efficient residual‐based a posteriori error estimate, which is robust with respect to the plate's thickness. Numerical evidence for this and the efficiency of the new algorithm is provided in the sense that non‐optimal convergence rates are optimally improved in our numerical experiments. Copyright © 2003 John Wiley & Sons, Ltd.     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.