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.     

Adaptive fuzzy control for nontriangular form systems with time-varying full-state constraints

This article investigates an adaptive fuzzy tracking control problem for a class of nontriangular form systems with asymmetric time-varying full state constraints. Unknown functions are approximated by the fuzzy logic systems. A domination approach is employed to tackle the nontriangular form structure. Time-varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure full-state constraints satisfaction. Based on the backstepping technique and time-varying ABLFs, an adaptive controller is proposed and guarantees that all the signals in the closed-loop system are ultimately bounded and the time-varying full state constraints are met. Simulation examples are presented to further demonstrate the effectiveness of the proposed approach.     

非测绘专业"测量学"课程的探讨

探讨了非测绘专业中测量学课程教学改革的问题,结合我院实际情况,从教学内容、教材的选用、教学方法、实验实习教学环节等方面进行讨论,希望能起到一定的借鉴作用。     

关于中值定理的几点应用

本文作者给出了在两种不同类型的证明题中应用中值定理的方法.这些方法简单、实用.     

基于改进模糊综合评价法的水利工程社会评价研究

通过对水利工程社会评价及模糊综合评价法的介绍,讨论了模糊层次分析法中的一致性检验问题,并采用改进的模糊综合评价法对江垭水利枢纽工程进行社会评价,得到综合评价结果。     

信息安全风险评估的模糊多准则决策方法

基于ISO/IEC17799标准建立了一个综合的信息系统风险分析框架,并运用模糊多准则决策(FMCDM)方法计算信息安全风险,根据风险等级矩阵(RLM)对信息资产风险进行级别划分,最终建立评估信息资产相关风险的完整模型。     

光传送网中客户信号的映射和复用

文章主要介绍了光传送网(OTN)中光传输模块(OTM)的映射、复用结构、光通道数据单元(ODUk)的时分复用以及客户信号的映射方法．     

多标准视频硬件解码器的存储器地址映射方法

提出了一种支持多标准视频的存储器地址映射方法,用一个简洁的公式把视频图像映射到DDR SDRAM的存储空间.该方法兼顾运动补偿模块、去块效应滤波模块(或重建模块)和显示模块的不同需求特点,通过充分减少DDR SDRAM非读写命令的额外延时,达到较高的存储器接口效率.     

An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

1　IntroductionIndesigningacomputercommunicationnet work ,thenetworkaveragedelayisanimportantpa rameterinthenetworkperformance .Inthispaper,weonlyconsiderM /M/1networks,whichmeansthatthemessageprocessingtimeisaprobabilisticdensityfunctionwithnegativepower,thegroupar rivalandsendingisofPoissiondistributionwithasinglequeue .Supposethatthenetworktopologicalstructureandtheestimatesoftheexternaltrafficrequirementsaregiven ,howtoselecttheoptimalroutestobeusedbythecommunicatingnodesinthenetworksoast…     

模糊层次分析法在腐蚀影响因素分析中的应用

结合国内外对碳钢CO2腐蚀影响因素的研究成果,采用模糊层次分析法对影响输油管道 CO2腐蚀的因素进行定量分析,明确界定出这些因素对二氧化碳腐蚀影响的相对重要性(权重),为后续制定经济有效的管道内腐蚀防护措施提供了客观依据。