二维模糊控制器在小型轮式机器人中的应用

为了提高小型轮式机器人电机系统的运行性能,设计了一种带修正函数的二维模糊控制器.首先阐述模糊控制器的基本结构,并结合具体控制对象设计了fuzzy论域和模糊控制规则;其次设计了实现该控制器的嵌入式平台.最后给出了实验结果,实验证明了该模糊控制器的有效性.     

模糊诊断隶属度函数系数的机器自学习方法

模糊诊断方法就是根据某些症状的隶属度来求出各种故障的隶属度.文中采用计算机自适应的最小二乘优化方法实现模糊诊断系统隶属度函数的机器自学习功能.     

基于免疫强化学习机制的多机器人动态协作

利用免疫系统中T细胞对抗体的调节作用，本文提出的免疫强化学习方法以强化学习形式，动态调整抗体间相互作用系数，优化网络结构，充分利用了免疫系统的自学习、自适应和免疫记忆特性。将免疫强化学习应用于机器人系统，机器人基于行为集，在实际运行中在线学习未知环境信息，优化行为选择。在基于免疫学习的单机器人系统基础上，考虑多机器人协作性，并应用于多机器人多目标探测中。仿真验证了基于免疫学习机制的多机器人系统对未知动态环境的学习能力和动态协作的有效性。     

二级模糊综合评判在企业订单评估中的应用

针对现行企业订单评估中常受到非重要因素影响的问题,在现有方法的基础上,提出了一种更优的隶属度函数来建立模糊评判矩阵中的元素值,并论证确定该隶属度函数的合理性,同时给出了应用该隶属度函数确定的模糊评判矩阵的一个实例.即用二级模糊综合评判方法来评估的企业订单评估指标体系,在一定程度上减少了非重要因素的影响,提高了对企业调度...     

模糊控制器在电炉温度控制系统中的应用

介绍了模糊控制器算法设计及其在工业生产过程控制中的应用，所设计的系统工作稳定性和可靠性较好。     

一种模糊控制器在非最小相位系统中的应用

针对非最小相位系统具有右半平面零点，系统阶跃响应存在负调．以及常规方法控制不理想等问题，在分析常规模糊控制器的基础上设计了一种模糊积分控制器，改善了模糊控制器的动态和稳态性能。仿真结果证实了模糊积分控制器的可行性。     

基于强化学习的机器人操作手轨迹规划方法研究

由于机器人操作手具有高度非线性、强耦合和变结构的动态特性,因此,利用传统控制理论很难实现对机器人操作手的有效控制.文章对基于径向基函数网络的强化学习在机器人操作手的多智能体环境中的轨迹规划进行了研究.仿真实验结果证明了研究方法的可行性.     

基于不同隶属度函数的金属材料切削加工性模糊综合评价

随着各种高性能工程材料的不断出现,为快速准确地制定这些材料的加工工艺,需要可靠地评估其切削加工性。目前常用且合理的评价方法是模糊综合评价法,确定最佳隶属度函数是其关键。本文分别构建正态型和分段型隶属度函数模型,对8种金属材料的可加工性进行模糊综合评价。结果表明:正态型隶属度函数所含参数较多且计算较复杂,但模糊综合评价结果优于基于分段型隶属度函数的结果;分段型隶属度函数形式简单,所含参数较少且计算较为快捷;当评价因素远离非模糊子集边缘区域时,评价结果与基于正态型隶属度函数的模糊综合评价结果一致。     

模糊神经网络技术及其在机器人中的应用

阐明模糊和神经网络技术的结合形式,二者与人工智能技术的关系;介绍模糊神经网络在机器人控制中的应用——并联机器人自适应力控制器。针对医用骨科机器人,谈谈模糊神经网络技术在研究中应用的可能性。     

模糊集合论在机械可靠性设计中的应用

本文将模糊集合理论应用在机械可靠性设计上，建立了机械模糊随机可靠性的数学模型，讨论了机械零件正常工作这一模糊随机事件隶属函数的确定方法，并以实例具体说明模糊随机可靠度的计算方法。     

High-order interval type-2 Takagi-Sugeno-Kang fuzzy logic system and its application in acoustic emission signal modeling in turning process

Type-2 fuzzy logic systems (FLSs) are gaining in popularity because of their capacity to handle rule uncertainties in a more complete way. Moreover, higher-order interval type-2 (IT2) FLS can reduce drastically the number of rules needed to perform the approximation and improve transparency and interpretation in many high-dimensional systems. This paper presents architecture and inference engine of generalized IT2 Takagi-Sugeno-Kang (TSK) FLS and the design method of higher-order IT2 FLS. An experimental acoustic emission (AE) signal modeling using a second-order IT2 TSK FLS in turning process is given to demonstrate the differences between the first-order and second-order IT2 FLSs and the advantage and efficiency of high-order IT2 FLS. The estimation of uncertainty of AE could be of great value to a decision maker and used to investigate tool wear condition during the machining process.     

A two-stage servo feed controller of micro-EDM based on interval type-2 fuzzy logic

In order to improve the performance of micro-electrical discharge machining (micro-EDM), the most important issue is to develop a highly stable servo control system. In order to account for the characteristics of high frequency, serious signal distortion, and high noise in micro-EDM process, type-2 fuzzy logic sets are introduced which is able to handle these uncertainties effectively. Based on interval type-2 fuzzy sets theory, a two-stage servo feed controller is designed. The first stage of the controller is for detecting the discharge state for a single sample point, and the second stage is used to obtain the servo feed speed. In addition, the discrimination and statistical methods for discharge states of sample points are proposed to obtain the proportion of each discharge state in an analytical period. Experiments demonstrate that the new controller can obviously improve the processing efficiency of micro-EDM compared with traditional controllers. Therefore, the proposed interval type-2 fuzzy logic-based two-stage servo feed controller is an effective way to enhance the efficiency and stability of micro-EDM and meanwhile to achieve good processing quality.     

A simplified type-2 fuzzy logic controller for real-time control

Increasingly, genetic algorithms (GAs) are used to optimize the parameters of fuzzy logic controllers (FLCs). Although GAs provide a systematic design approach, the optimization process is generally performed off-line using a plant model. Differences between the model and physical plant may result in unsatisfactory control performance when the FLCs are deployed in practice. Type-2 FLCs are an attractive alternative because they can better cope with modeling uncertainties. Unfortunately, type-2 FLCs are computationally intensive. This paper presents a simplified type-2 FLC that is suitable for real-time applications. The key idea is to only replace some critical type-1 fuzzy sets by type-2 sets. Experimental results indicate that the proposed simplified type-2 FLC is as robust as a conventional type-2 FLC, while lowering the computational cost.     

未知环境中基于强化学习的移动机器人路径规划

为解决未知环境中移动机器人的自适应路径规划问题,提出了一种基于Q学习算法的自主学习方法。首先设计了未知环境中基于传感器信息的移动机器人自主路径规划的学习框架,并建立了学习算法中各要素的数学模型;然后利用模糊逻辑方法解决了连续状态空间的泛化问题,有效地降低了Q值表的维数,加快了算法的学习速度;最后在不同障碍环境中对基于Q学习算法的自主学习方法进行了仿真实验,仿真实验中移动机器人通过自主学习较好地完成了自适应路径规划。研究结果证明了该自主学习方法的有效性。     

自校正模糊控制器及其应用

本文介绍自校正模糊控制器的结构和设计方法，并给出工业窑炉恒温模糊控制的实例。     

基于行为的机器人自学习方法研究

随着机器人智能化的不断发展,行为机器人越来越受到人们的重视。而复杂多变的运行环境,给机器人的行为设计提出了一个很大的难题。根据以往的日常经验总结出来的行为反应规则很可能适应不了各式各样的运行环境。本文提出一种机器人在线自学习方法,使机器人在没有现成的合适运行规则可循的环境运行的过程中不断总结经验,自我学习,并对学习得到的成果进行检验。实验时,不给机器人初始化任何路径规划信息,而是通过让机器人在简单环境下自行运动,由得到的实际运行结果,检验本方法的实际效果。检验结果令人满意。     

A type-2 fuzzy expert system based on a hybrid inference method for steel industry

In this paper, a novel type-2 fuzzy expert system for prediction the amount of reagents in desulfurization process of a steel industry in Canada is developed. In this model, the new interval type-2 fuzzy c-regression clustering algorithm for structure identification phase of Takagi–Sugeno (T–S) systems is presented. Gaussian Mixture Model is used to generate partition matrix in clustering algorithm. Then, an interval type-2 hybrid fuzzy system, which is the combination of Mamdani and Sugeno method, is proposed. The new hybrid inference system uses fuzzy disjunctive normal forms and fuzzy conjunctive normal forms for aggregation of antecedents. A statistical test, which uses least square method, is implemented in order to select variables. In order to validate our method, we develop three system modeling techniques and compare the results with our proposed interval type-2 fuzzy hybrid expert system. These techniques are multiple regression, type-1 fuzzy expert system, and interval type-2 fuzzy TSK expert system. For tuning parameters of the system, adaptive-network-based fuzzy inference system is used. Finally, neural network is utilized in order to reduce error of the system. The results show that our proposed method has less error and high accuracy.     

基于AS-UII机器人的移动学习通信系统的设计

移动学习日益成为现代教育技术研究者关注的新方向,本文针对当前移动学习应用研究存在的学习资源不系统化,学习方式不智能化,学习环节缺乏交互性等问题,开发了基于AS-UII机器人的移动学习通信系统,该系统具有专家解答能力、无线通讯能力和人机语音交互能力.实验采用从哈尔滨工业大学引进的AS-UII机器人作为开发平台,控制系统采用武汉创维特公司的一款基于S3C44B0X处理器的EB44B0开发板,成功的模拟了基于AS-UII机器人的移动学习系统.将AS-UII机器人引入教育应用领域是一次全新的尝试和探索.     

基于模糊逻辑的机器人非标定视觉路径规划

本文提出了一种基于模糊控制的对含不确定性的移动机器人的非标定视觉伺服路径规划控制方法。本方案将摄像机固定于移动机器人工作区域内,运用摄像机针孔模型设计了一种新的非标定机器人视觉伺服路径跟踪系统,在此系统下运用模糊控制理论设计了模糊控制器,在视觉伺服系统参数未标定的前提下完成了对含不确定性参数的移动机器人视觉伺服路径规划。仿真实验证实控制效果良好。     

Trajectory and vibration control of a flexible joint manipulator using interval type-2 fuzzy logic

This study presents the development of a novel interval type-2 fuzzy logic controller for real time trajectory and vibration control of a flexible joint manipulator. The controller is designed on the Mamdani based interval type-2 fuzzy logic toolbox, which is developed by the authors, using interval triangular membership functions and Karnik–Mendel type reduction algorithm. The closed-loop stability of the system is proved based on Lyapunov stability theorem. In order to observe the effectiveness and robustness of the proposed controller to variations of system parameters (change in link length and payload), the experimental results of interval type-2 and conventional type-1 fuzzy logic controllers are compared. The results show that proposed controller clearly improves the link vibration and trajectory tracking behavior of the system.