热压成型装备精密温控研究

为了提高热压装备的温度控制精度,采用热电致冷器作为温度控制的主控元件构建了热压成型系统。针对热电致冷器呈现的复杂热电特性,在对其模型进行小信号线性化的基础上,获得了热电致冷器的控制模型。结合传统PID控制和模糊控制的优点,根据热电致冷器的非线性和可能的不确定性因素,建立PID参数自调整的推理规则,设计了热压成型装备温控的模糊PID控制器。阶跃响应实验表明该温控系统具有良好的动态性能和稳态品质,其升降温速度不小于1℃/s,温控精度可达0.2℃,满足热压成型装备精密温控的要求。     

Prognostication of vertical stress transmission in soil profile by adaptive neuro-fuzzy inference system based modeling approach

Prediction of vertical stress transmission in real soil profile using adaptive neuro-fuzzy inference system (ANFIS) is documented in this investigation. A soil bin facility holding a single-wheel tester was utilized to arrange controlled condition for exploration of the effects of wheel load, forward velocity, slippage and depth each at three different levels. A profile housing seven load cells was buried at different depths when data were transmitted to a data acquisitioning system for derivation of 81 data points and then to build ANFIS-based model. The Sugeno-type fuzzy rules were constituted with various membership functions in the representations. In the Sugeno-type fuzzy inference approach, the modal was developed according to the four input parameters. Performance evaluation criteria (i.e. MSE, MRE and R²) were incorporated in the study to find the highest quality solution. It was deduced, on the basis of performance criteria, that a Guassian membership function outperformed other tested membership functions. The results could serve as a catalyst to expedite the investigations in the realm of artificial intelligence application in prediction of soil stress transmission created by wheeled vehicle trafficking.     

近室温样品加热炉温度的模糊PID控制研究

根据红外隐身材料光谱发射率测试方法的要求,提出了一种基于半导体制冷器的近室温样品加热炉系统。在对加热炉系统特性进行分析的基础上,建立了基于模糊PID控制的系统仿真模型。经仿真及实验可知,在加热和制冷条件下,实际温度与设定温度之间的误差分别为±0.20℃和±1.00℃。结果表明,系统稳定性好,响应时间短,解决了近室温样品加热炉抗干扰能力弱、不易控制等问题。     

自适应神经模糊推理系统在倒立摆控制中的应用

针对单级倒立摆系统具有多变量、非线性、绝对不稳定的特点,应用Matlab/Simulink设计了用于倒立摆系统的、基于自适应神经模糊推理系统的ANFIS控制器,采用反向传播算法和最小二乘算法的混合算法对倒立摆控制样本数据进行学习,调整各变量的隶属度函数,自动产生模糊规则.仿真结果表明,ANFIS控制器对倒立摆系统的摆杆角度和小车位置的控制过程具有良好的动态性能和稳态性能.     

应用热电制冷器的微型航天器主动温度控制及仿真

为了改善微型航天器的温度控制效果,介绍了一种应用热电制冷器的主动温度控制系统,建立了这种温度控制系统受控对象及辐射器温度变化的动态特性模型,并对受控对象内部热源功率发生变化时的温度控制效果进行了仿真分析。仿真结果表明：热电制冷器和PI控制器相结合可以简便有效地完成微型航天器内部电子设备的温度控制任务,动态特性模型为这种温度控制系统的优化设计提供了简便的数学模型。     

一种基于自适应模糊神经网络的交通灯控制系统

交通灯控制是智能交通系统的一个重要部分,针对我国中等城市交通流具有模糊性、复杂性的特点,将模糊逻辑和神经网络相结合,采用模糊隶属函数来描述车辆排队长度和绿灯时间,建立了模糊神经网络交通灯信号控制模型。利用神经网络等技术对交通系统进行全局优化调度,并在此基础上形成调度指令,利用模糊控制的方法实现交叉口的交通灯控制。     

Neural network controller for robotic motion control

Since a robotic manipulator has a complicated mathematical model, it is difficult to design a control system based on the complicated multi-variable nonlinear coupling dynamic model. Intelligent controllers using fuzzy and neural network approaches do not need a real mathematical model to design the control structure and have attracted the attention of robotic control researchers recently. A traditional fuzzy logic controller does not have learning capability and it needs a lot of effort to search for the optimal control rules and the shapes of membership functions. Owing to the time-varying behaviour of the system, the required fine tracking accuracy is difficult to achieve by adjusting the fuzzy rules only. The implementation problems of neural network control are the initial training and initial transient stability. In order to improve the position control accuracy and system robustness for industrial applications, a neural controller is first trained off-line by using the input and output (I/O) data of a traditional fuzzy controller. Then the neural controller is implemented on a five-degrees-of-freedom robot with a back propagation algorithm for online adjustment. The experimental results show that this neural network controller achieved the required trajectory tracking accuracy after 15 on-line operations.     

半导体制冷/制热试验箱性能模拟和调节

微型橡胶材料试验箱拟采用半导体制冷／制热技术进行箱内温度工况的调节和控制,通过建立数学模型、模拟子系统,采用Matlabl／Simulink软件对系统进行性能模拟和调试,得出了几种调节方法下系统主要参数的动态和稳态过程,并简要分析了环境温度对调节参数的影响。模拟方法和结果对于系统设计、系统调试有一定指导作用。     

基于模糊神经网络信息融合的采煤机煤岩识别系统

针对采用单一信号进行煤岩界面识别实现采煤机滚筒高度调整控制时精确度和可靠性不高的问题,提出一种基于模糊神经网络的多传感器信息融合煤岩识别方法。通过实验数据采集和分析得到不同煤岩比例截面截割过程中的振动、电流以及声功率谱信号特征样本,根据最小模糊度优化模型求得各煤岩识别信号的模糊隶属度函数,采用基于自适应神经网络模糊推理系统构建的多维模糊神经网络实现多传感器信息的决策融合,得到高可信度和精确度的滚筒调高控制量值。实验室截割实验对比以及现场随机煤岩轨迹的截割实验结果表明,采煤机滚筒截割轨迹与实际随机煤岩轨迹基本吻合,实验结果验证了系统的有效性和可靠性。     

基于神经模糊技术的电液伺服控制

研究了基于神经模糊混合技术的电液伺服系统控制问题。综合神经网络与模糊逻辑技术的优势,构造了一种神经模糊控制器,它具备知识自动获取、并行分布存储及快速模糊推理决策的能力,给出了一种在线学习算法。用于一类典型的电液伺服系统的控制,获得了满意的效果。神经模糊混合技术对于电液伺服控制的发展与要求（如更复杂系统及其高性能控制）具有重要价值。     

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.     

Investigating the effects of hard anodizing parameters on surface hardness of hard anodized aerospace AL7075-T6 alloy using fuzzy logic approach for fretting fatigue application

Aerospace applications and energy saving strategies in general raised the interest and study in the field of lightweight materials, especially on aluminum alloys. Aluminum alloy itself does not have suitable wear resistance. Therefore, improvements of surface properties are required in practical applications, especially surface hardness when aluminum is in contact with other parts. In this work, first Al7075-T6 was coated using hard anodizing technique in different parameters condition and the surfaces hardness of hard anodizing-coated specimens were measured using microhardness machine. Second, fretting fatigue life of AL7075-T6 was investigated for both uncoated and hard anodized specimens at the highest surface hardness obtained. Third, a fuzzy logic model was established to investigate the effect of hard anodizing parameters, voltage, temperature, solution concentration, and time on the anodized AL7075-T6. Four fuzzy membership functions are allocated to be connected with each input of the model. The results achieved via fuzzy logic model were verified and compared with the experimental result. The result demonstrated settlement between the fuzzy model and experimental results with 95.032 % accuracy. The hardness of hard anodizing-coated specimens was increased up to 360 HV, while the hardness of uncoated specimens was 170 HV. The result shows that hard anodizing improved the fretting fatigue life of AL7075-T6 alloy 44 % in low-cycle fatigue.     

应用于起重机稳钩控制的自适应神经模糊推理系统

提出一种基于自适应神经模糊推理系统（ANFIS）的控制方法应用于起重机的稳钩控制,该方法采用反向传播算法（BP）和最小二乘算法（LS）的混合算法对小车—吊重系统样本数据进行学习,调整各变量的隶属度函数,自动产生模糊规则。仿真结果表明,这种控制方法对小车—吊重系统的摇摆角度和小车位置的控制过程具有良好的动态性能和较强的鲁棒性能,说明了自适应神经模糊推理系统在起重机稳钩控制中的有效性。     

基于Cortex-M0的半导体制冷温度控制系统设计

冷凝露点法是一种高精度的食品水分活度检测方法,温度控制是其关键技术之一。本设计采用最新型Cortex-M0内核芯片LPC1114作为控制单元,选用半导体制冷器和加热器作为温度控制元件,运用数字PID智能算法进行温度控制。可用于水分活度测量辅助实验,精度高、响应快,取得良好的控制效果。     

基于遗传算法的模糊振动主动控制器的参数编码设计和约束处理

在采用模糊控制的压电材料智能结构中,利用遗传算法对模糊控制隶属函数进行优化时,遗传编码的设计将影响优化结果,从振动主动控制要求出发,设计了振幅输入模糊集的隶属函数参数编码,并对模糊子集约束条件进行处理。结果表明新的编码方式可以产生适合振动主动控制的隶属函数,且设计的约束修补算法简单有效。     

Design of Fuzzy Logic Controlled Thermoelectric Renal Hypothermia System

Abstract

In this study, a fuzzy logic controlled Thermoelectric Renal Hypothermia System has been implemented for use in renal surgery. Herein, temperature control of the Thermoelectric Renal Hypothermia System has been carried out via a Fuzzy Logic Controller. Since the most important issues in long‐lasting parenchymatous renal surgery are to provide an operation medium that is free of blood and to prevent renal dysfunction in the postoperative period, control of the temperature has become very important in renal surgery. The final result is seriously affected by changes in temperature; therefore, it is necessary to reach some desired temperature points quickly and to avoid a large overshoot. The PIC16F877 microcontroller has been used as the fuzzy logic controller. The designed system is energy saving, decreases temperature swings to a minimum level; so, it offers efficient results. Also, the designed system takes into consideration appropriate parameters that can reflect very small changes in the kidney and can be applied to people safely in the future.     

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...     

基于Cortex—M0的半导体制冷温度控制系统设计

冷凝露点法是一种高精度的食品水分活度检测方法,温度控制是其关键技术之一。本设计采用最新型Cortex-M0核芯LPC1114作为控制单元,选用半导体制冷器和加热器作为温度控制元件,运用数字PID智能算法进行温度控制。可用于水分活弗则量辅助实验精度高、响应陕,取得良好的控制效果。     

Diagnosing planetary gear faults using the fuzzy entropy of LMD and ANFIS

The small size, low weight, and large transmission ratio of planetary gear have resulted in large-scale use, low speed, and heavy-duty mechanical systems. Poor working conditions of planetary gear lead to frequent occurrence of faults. A method is proposed for diagnosing faults in planetary gear based on fuzzy entropy of Local mean decomposition (LMD) and Adaptive neuro-fuzzy inference system (ANFIS). The original vibration signal is decomposed into six Product function (PF) components and a residual using LMD. Given that decomposed PF components contain the main fault feature information, fuzzy entropy is used to reflect the complexity and irregularity of each PF component. The fuzzy entropies of each PF component are defined as the input of the ANFIS model, and its parameters and membership functions are adaptively adjusted based on training samples. Finally, fuzzy inference rules are determined, and the optimal ANFIS model is obtained. Testing samples are used to verity the trained ANFIS model. The overall fault recognition rate reaches 88.8%, and the fault recognition rate for gear with wear reaches 96%. Therefore, the proposed method is effective at diagnosing planetary gear faults.     

数控机床切削用量的模糊控制

阐述了在数控机床上使用模糊控制理论,对切削用量做出合理选择并使其达到最优值的一种方法。首先,利用模糊控制原理,结合数控机床实际,将切削力、毛坯材料、主轴转速、切削温度作为输入,进给速度、背吃刀量作为输出,设计出相应的模糊控制推理框图,展示推理过程;其次,依据推理框图和数控机床输入、输出条件,制订模糊推理规则,提出输入量检测的方法,推导出输入条件和输出条件的隶属度函数并以图形展示,定义输入、输出条件的模糊量子集;最后,根据输入、输出条件和模糊推理规则,构造出模糊控制规则表,实现了采用人类语言、模拟人类思维的控制方式。