聚类算法分析及在GIS中心选址中的仿真研究

通过对聚类算法初始点选择策略的分析和比较,经典k-means算法在GIS海量数据处理上的效率问题,提出了随机采样的k-means算法来进行坐标聚类;并将随机采样k-means算法应用于GIS中心选址,充分利用GIS数据分析和处理能力,以城市间的欧几里得距离为相似条件,采用最大最小原则选取初始点进行聚类,从而缓解局部最优解产生的概率;选取中心城市作为目标对象,从而提高商业决策的充分性和可靠性;经仿真结果验证了所提出的随机取样k-means算法的有效性和正确率。     

模糊聚类有效性的研究进展

聚类有效性评价对聚类分析具有重要意义,是聚类分析的瓶颈之一。本文从基于数据集模糊划分的方法和基于数据集几何结构的方法两方面,归纳综述了常用的模糊聚类有效性评价函数,并讨论了模糊聚类最佳类别数的自动确定问题。     

测距传感器数据在线自适应加权融合

针对移动机器人的测距系统,采用了红外线传感器与超声波传感器共同测距,避免了因使用单个传感器进行多次测量而降低系统的实时性和产生信号串扰问题;应用自适应加权数据融合估计算法对实时测量数据进行在线融合估计,只对当前采样时刻的测量数据进行自适应加权融合,而各传感器的加权因子则通过传感器的测量数据进行方差在线学习估计以自适应方式进行调整,使融合结果的均方误差始终最小,实现两种传感器在功能上的互补;实验结果表明,该方法提高了整体测距精度,得到了被测距离更加准确的估计.     

基于工控组态软件的模型参考自适应液位控制系统的设计

针对FESTO过程控制系统液位站中的液位控制问题,提出了一种利用工控组态软件和ActiveX特性扩充组态软件控制功能实现模型参考自适应控制的新方法;重点描述了控制策略、现场信号和组态软件之间的有机结合,为在工业控制领域中使用组态软件来完成复杂的控制算法开辟了新的途径;从实验结果的两组响应曲线可以看出,采用自适应控制时系统的性能指标要优于常规PID控制;因此,可以证明文中设计的自适应控制系统可以实现对液位的稳定控制;系统具有形象直观、实时性好、编程简单等特点,满足了工业控制的要求。     

多模型自适应控制的空分系统整体能耗优化

运用多模型自适应控制技术,针对空分系统的整体能耗优化,就空分系统模型集的建立、控制器的设计、切换算法等方面进行了分析。空分系统作为一个实时变化的有机整体,在整体运行过程中存在的操作环境改变对系统的影响,当系统发生变化及波动时,根据相应切换算法切换到可以满足生产变化的模型,采用适合的控制器,以达到实时监控、安全生产的效果,最大限度地优化了系统运行。     

基于聚类和支持向量机的话务量预测模型

针对利用单因素时问序列模型进行话务量预测的不足,建立基于模糊C均值(FCM)聚类和支持向量机(SVM)的多元回归话务量预测模型.模型使用FCM算法对话务量的原始样本集聚类,选择与待预测样本特征最相似的样本子集作为训练集.使用SVM训练样本,通过决策回归函数预测话务量.实际话务量数据验证表明,该方法较周期时间序列和神经网络预测方法具有更高的预测精度和泛化能力.     

永磁同步电机的自适应反演滑模变结构控制

针对永磁同步电机提出一种基于反演的PMSM自适应滑模控制方案.设计基于反演的滑模变结构位置控制器,通过RBF神经网络实现系统参数变化和外部负载扰动等引起的不确定上界值的在线辨识,减小滑模控制器的控制量,并引入饱和函数来减弱系统的"抖动"现象.理论分析和仿真结果对比表明,基于RBF神经网络的自适应反演滑模控制对参数变化和外部负载扰动具有很好的鲁棒性,永磁同步电动机获得了很好的跟踪效果.     

Robust output feedback learning control for induction motor servo drives

This paper addresses the output feedback tracking control problem for induction motor servo drives with mechanical uncertainties: rotor angle, rotor speed and stator currents are assumed to be available for feedback. A robust adaptive learning control is designed under the assumption that the reference profile for the rotor angle is periodic with known period: it ‘learns’ the periodic disturbance signal by identifying the Fourier coefficients of any truncated approximation; ??₂ and ??_∞ transient performances are guaranteed in the ‘learning phase’. It is shown that, for any motor initial condition belonging to an arbitrary given compact set, by properly setting the control parameters: (i) the rotor position and flux modulus tracking errors exponentially converge to residual sets, which may be arbitrarily reduced by increasing the number of terms in the truncated Fourier series; (ii) when the unknown periodic disturbance can be represented by a finite Fourier series, the rotor position and flux modulus tracking errors exponentially converge to zero. As in field oriented‐control, the control algorithm generates references for the magnetizing flux component and for the torque component of the stator current leading to significant simplifications for current‐fed motors. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive control design for a class of nonsmooth nonlinear systems with matched and linearly parameterized uncertainty

This paper presents an adaptive control design for a class of nonsmooth nonlinear systems with matched uncertainty, which is linearly parameterized with a known discontinuous function. The design framework is based on the concept of the Filippov solution as the classical Lyapunov theory for smooth systems cannot be applied to establish the stability of the adaptive control system due to the presence of the discontinuity. It is proved that as an adaptive control system, the global Lyapunov stability with the convergence of the state of the controlled system to the origin can be achieved by evaluating the monotonicity of the Lyapunov function in the state space, particularly on the discontinuous surface, while the uniqueness of the solution of the closed‐loop system is not necessarily guaranteed. Some interesting numerical examples are demonstrated with simulation results. Copyright © 2008 John Wiley & Sons, Ltd.     

Adaptive integral method combined with the loose GMRES algorithm for planar structures analysis

In this article, the adaptive integral method (AIM) is used to analyze large‐scale planar structures. Discretization of the corresponding integral equations by method of moment (MoM) with Rao‐Wilton‐Glisson (RWG) basis functions can model arbitrarily shaped planar structures, but usually leads to a fully populated matrix. AIM could map these basis functions onto a rectangular grid, where the Toeplitz property of the Green's function would be utilized, which enables the calculation of the matrix‐vector multiplication by use of the fast Fourier transform (FFT) technique. It reduces the memory requirement from O(N²) to O(N) and the operation complexity from O(N²) to O(N log N), where N is the number of unknowns. The resultant equations are then solved by the loose generalized minimal residual method (LGMRES) to accelerate iteration, which converges much faster than the conventional conjugate gradient method (CG). Furthermore, several preconditioning techniques are employed to enhance the computational efficiency of the LGMRES. Some typical microstrip circuits and microstrip antenna array are analyzed and numerical results show that the preconditioned LGMRES can converge much faster than conventional LGMRES. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.