Learning fuzzy controllers in mobile robotics with embedded preprocessing

The automatic design of controllers for mobile robots usually requires two stages. In the first stage, sensorial data are preprocessed or transformed into high level and meaningful values of variables which are usually defined from expert knowledge. In the second stage, a machine learning technique is applied to obtain a controller that maps these high level variables to the control commands that are actually sent to the robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learning stage in order to get controllers directly starting from sensorial raw data with no expert knowledge involved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules (QFRs), that are able to transform low-level input variables into high-level input variables, reducing the dimensionality through summarization. The proposed learning algorithm, called Iterative Quantified Fuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with different structures, and can manage linguistic variables with multiple granularities. The algorithm has been tested with the implementation of the wall-following behavior both in several realistic simulated environments with different complexity and on a Pioneer 3-AT robot in two real environments. Results have been compared with several well-known learning algorithms combined with different data preprocessing techniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover, three real world applications for which IQFRL plays a central role are also presented: path and object tracking with static and moving obstacles avoidance.     

An element-based displacement preconditioner for linear elasticity problems

Finite element analysis of problems in structural and geotechnical engineering results in linear systems where the unknowns are displacements and rotations at nodes. Although the solution of these systems can be carried out using either direct or iterative methods, in practice the matrices involved are usually very large and sparse (particularly for 3D problems) so an iterative approach is often advantageous in terms of both computational time and memory requirements. This memory saving can be further enhanced if the method used does not require assembly of the full coefficient matrix during the solution procedure. One disadvantage of iterative methods is the need to apply preconditioning to improve convergence. In this paper, we review a range of established element-based preconditioning methods for linear elastic problems and compare their performance with a new method based on preconditioning with element displacement components. This new method appears to offer a significant improvement in performance.     

Clay compaction modelling by homogenization theory

The modelling of hydromechanical behavior of clayey sediments by homogenization theory is described. The rheological model of clays buried in depth requires a three-dimensional approach and laboratory experiments to quantify the model parameters. An iterative process which can be coupled to any homogenization method is used to model the porous media behavior. Hydromechanical compaction results from oedometric experiments are simulated with the proposed model.     

最大熵重建的迭代凸I投影算法

本文探讨了用迭代凸Ｉ投影（ＩｔｅｒａｔｉｖｅＣｏｎｖｅｘＩ－Ｐｒｏｊｅｃｔｉｏｎ，ＩＣＩＰ）算法求解最大熵Ｘ－ＣＴ重建问题．其思路是将这个复杂问题转化为多个简单子问题，然后迭代地求解这种单约束子问题．理论证明，这种算法收敛并能收敛到问题的最大熵解．这种算法形式优美，仿真结果表明算法同时也是有效的．     

用于非均匀介质重建的选代算法收敛性的研究

研究轴对称二维非均匀介质重建迭代算法的收敛性问题。首先借助于玻恩近似将非线性积分方程线性化，然后，利用玻恩迭代法和变形玻恩迭代法，由散射场数据对轴对称二维非均匀介质进行重建。通过几个例子研究了影响迭代算法收敛性的几种因素，如送代算法本身、积分离散化后的网格划分、正则化方法中的正则化参数选取等。     

迭代回归法计算T型电位滴定中试液含量

本文将迭代回归法计算Ｔ型电位滴定中，叙述了其原理及数学推导，并运算了一批实验数据，结果表明，该法准确度较高，且不需空白溶液校正。     

倒虹吸管管径计算的迭代法

本文先将倒虹吸管的管径计算公式整理成等式左边只含管径的一次方法，右边含有管径高阶非线性的迭代函数，然后证明该迭代函数收敛，最后利用数学迭代原理给迭代函数右边赋初值，计算左边的管径。继续迭代下去，就能求出倒虹吸管的管径。     

加速SPICE进行三维电磁分析

互连结构的电磁分析越来越受到人们的重视.针对三维互连,A.E.Ruehli提出了部分元等效电路法.但该法生成的等效电路具有紧耦合性,用SPICE进行分析时稀疏矩阵技术已失去原先的优越性.本文采用广义残量法作为大型紧耦合线性方程组的求解工具以取代SPICE中的LU分解法,并辅以初值预估.实际计算表明,本文的方法提高了运算速度.广义残量法也可用于矩量法的方程求解中.     

Identification of delayed system using instrumental variable method

System identification uses system inputs and outputs to raise mathematical models.Various techniques of system identification exist that offer a nominal model and an uncertainty bound.Many practical systems such as thermal processes & chemical processes have inbuilt time delay.If the time delay used in the system model for controller design does not concur with the actual process time delay,a closed-loop system may be unstable or demonstrate unacceptable transient response characteristics so here the time delay is assumed to be time-invariant. This paper proposes on-line identification of delayed complex/uncertain systems using instrumental variable(Ⅳ) method.Parametric uncertainty has been considered which may be represented by variations of certain system parameters over some possible range.This method allows consistent estimation when the system parameters are associated with the noise terms,as the IV methods(IVM’s)usually make no assumption on the noise correlation configuration.The faster convergence of the parameters including noise terms has been proved in this paper.Iterative prefiltering(IP)method has also been used for the identification of the delayed uncertain system and the graphical results given in this paper demonstrate that the convergence results are inferior to the instrumental variable method.     

Stability analysis for discrete linear systems with state saturation by a saturation-dependent Lyapunov functional

This paper concerns the stability analysis problem of discrete linear systems with state saturation using a saturation-dependent Lyapunov functional.We introduce a free matrix characterized by the sum of the absolute value of each elements for each row less than 1,which makes the state with saturation constraint reside in a convex polyhedron.A saturation-dependent Lyapunov functional is then designed to obtain a sufficient condition for such systems to be globally asymptotically stable.Based on this stability criterion,the state feedback control law synthesis problem is also studied.The obtained results are formulated in terms of bilinear matrix inequalities that can be solved by the presented iterative linear matrix inequality algorithm.Two numerical examples are used to demonstrate the effectiveness of the proposed method.