Artificial hydrocarbon networks fuzzy inference systems for CNC machines position controller

This paper proposes a novel position controller for computer numerical control (CNC) machines based on a hybrid fuzzy inference system that uses artificial hydrocarbon networks in its defuzzification step, so-called fuzzy-molecular inference system. The fuzzy-molecular-based position controller is characterized to improve the accuracy in position and the time machining. In order to prove these characteristics, a case study was run over a reconfigurable micromachine tool (RmMT) assembly in lathe configuration. In addition, a workpiece machining in the RmMT assembly serves to realize a comparative analysis between the proposed controller and three other controllers: a classical PID controller manually tuned, a PID controller auto-tuned, and a fuzzy Mamdani controller. Experimental results validate the performance and the implementability of the proposed fuzzy-molecular position controller against the others.     

A fuzzy controller based on self-tuning rules for the nuclear steam generator water level

It was demonstrated that the fuzzy control method could be applied successfully to control and regulate the nuclear steam generator water level through previous works. However, this method has some limitations from the fact that its performance largely depends on the tuning method and how to settle the rule base. In this work, a fuzzy control algorithm based on self-tuning rules is investigated to find the optimal tuning point and to generate the control rule automatically. It adopts an on-line iterative method and the objective error function which contains the variation errors of all time-steps. The triangular membership functions based on the mass flow rate and water level errors are applied. And also, a forgetting factor is used to account for an exponential decay of the past data in tracking the slow drift in system parameters. Thus it controls the steam generator water level from low power to full power with a little transients. This control algorithm is validated by computer simulations.     

Electronic control of braking force distribution for vehicles using a Direct adaptive fuzzy controller

In brake systems, a proportioning valve(P. V), which reduces the brake line pressure on each wheel cylinder for the anti-locking of rear wheels, is closely related to the safety of vehicles. However, it is impossible for current P. V. s to completely control brake line pressure because, mechanically, it is an open loop control system. In this paper we describe an electronic brake force distribution system using a direct adaptive fuzzy controller in order to completely control brake line pressure using a closed loop control system. The objective of the electronic brake force distribution system is to change the cut-in-pressure and the valve slop of the P. V in order to obtain better performance of the brake system than with mechanical systems.     

Fuzzy-rule emulated networks, based on reinforcement learning for nonlinear discrete-time controllers

This article introduces an adaptive controller for a class of nonlinear discrete-time systems, based on self adjustable networks called Multi-Input Fuzzy Rules Emulated Networks (MIFRENs), and its reinforcement learning algorithm. Because of the universal function approximation of MIFREN, the first MIFREN called MIFREN(c) is used to estimate a long-term cost function, which demonstrates as a performance index for the tuning procedure. Another network or MIFREN(a) is designed as a direct controller via the human knowledge through defined If-Then rules. The selection procedure for any system parameters, such as learning rates and some constant parameters, is represented by the proof of proposed theorems. The system's performance is demonstrated by computer simulations via selected nonlinear discrete-time systems, and comparison results with other controllers to validate theoretical development.     

FCMAC在六自由度并联机构轨迹跟踪中的应用

六自由度并联机构控制系统中存在不确定性和非线性因素,使得对其轨迹跟踪的过程中会不断有误差产生.神经网络控制器以其在线自学习的功能,能实时反应并消除误差.用模糊理论对结构简单的小脑模型关节控制器(CMAC)的空间划分方式进行模糊化处理,并通过BP学习算法对CMAC的空间划分方式进行在线调整,所得到模糊小脑模型关节控制器(FCMAC)有更高的自适应能力.仿真实验结果表明,FCMAC的在线学习功能优于传统的CMAC;用FCMAC对六自由度并联构进行轨迹跟踪,能较好地消除误差,有较高的控制精度.     

A novel instrumented ring for the measurement of grip force adjustments during precision grip tasks

A wide range of scientific and clinical research studies use the measurement of grip force to quantify hand function and activities during daily living. Many applications of instrumented objects can be found in the biomechanical and neurophysiological literature. However, these were found not to be suitable for the measurement of grip force and force modulations during precision grip independently from the hand orientation. The low-cost precision grip force transducer described here is capable of recording magnitude, direction and modulation of the force exerted on a closed ring. The design is based on a standard proving ring, onto which a second set of strain gauges is applied. The outputs of both Wheatstone bridges yield a unique signature for every position under a two-point load. The tested aluminium ring had an outer diameter of 83 mm, a wall thickness of 3 mm and a height of 12 mm. With eight single bending strain gauges used, the maximum load was 100 N. During a grip task, tremor components from d.c. to 45 Hz could be detected. The newly developed ring might therefore find a use in many biomechanical and neurophysiological studies as a tool for measuring grip force and its fine modulations.     

水轮机调速器的模糊B样条基函数神经网络控制

水轮机调速器是控制水轮机输出机械功率的关键设备,是水轮发电机组控制的重要内容。针对非线性复杂时变的水轮机调速器,本文研究了一种模糊B样条基函数神经网络控制器。该智能控制器是一种模糊逻辑与神经网络控制器的结合,集中了二者的优点和长处。文章分析了该控制器的结构、具体实现以及学习优化。仿真实验表明该智能控制器的实际效果良好。     

Improved parallel scan method for nanofriction force measurement with atomic force microscopy

Based on Ruan and Bhushan's study [J. Ruan and B. Bhushan, J. Tribol. 116, 378 (1994)], an improved method for quantitative nano/microfriction force measurements with the atomic force microscope (AFM) is presented. The related theoretical derivation is given in detail. The coefficient of friction can be calculated by scanning in the direction parallel to the long axis of the AFM cantilever. Then conversion factor, which can convert the lateral deflection response of the photodetector into corresponding friction force, is identified with the Meyer and Amer method [G. Meyer and N. M. Ame, Appl. Phys. Lett. 57, 2089 (1990)]. Like Ruan and Bhushan method, the advantage of this approach is that the coefficient of friction can be obtained with the plan-view geometry of AFM cantilevers and some common uncertainties, such as thickness, coating, and material properties, are not necessary. The result of the experiments performed utilizing rectangular cantilevers of different lengths shows that this improved method produces an accurate agreement for cantilevers of different lengths, thus the method can be used to measure nano/microfriction force.     

Dispatching rules for unrelated parallel machine scheduling with release dates

A simplified procedure is proposed to predict the surface integrity of complex-shape parts generated by ball-end finishing milling. Along a complex cutting path, the tool inclination may vary within a large range. A geometrical study is performed to predict the effect of the tool inclination (lead angle) on the micro-geometry of the machined surface and on the effective cutting speed. This geometrical study brings out a range of values of the lead angle for which the machined surface is damaged by cutting pull-outs. This geometrical study also brings out a range of values of the lead angle for which the effective cutting speed is null. This case corresponds to extreme values of the cutting forces and to high compressive residual stresses. These predictions are verified for a selection of tool inclinations and other cutting parameters such as cutting speed, feed per tooth and cusp height. These machining tests are performed on a high-strength bainitic steel. The experimental campaign includes milling tests with cutting forces measurements, 2-D optical micro-geometry measurements and X-ray diffraction measurements.     

带触觉的肌电假手握力模糊控制方法

从注重残疾人本体感出发,提出了一种新的用于肌电假手握力控制的方法.该方法利用短时傅里叶变换思想对信号进行时间片分割,并对时间片内的信号分析选取了几个具有代表性的肌电信号参数,并用训练后的神经网络对其进行分析处理,进而估计出相应的肌肉用力大小.同时将肌电假手指端的力触觉传感器所得的力触觉信号和肌肉用力大小信号输入模糊控制器,根据设计好的模糊控制规则调节肌电假手驱动电机的转动速度从而控制握力大小.该方法可以有效减小个人差异性和肌电信号传感器检测位置不同对控制效果的影响,可以减小肌电传感器安装难度并可供不同的残疾人使用.实验结果证明了该握力控制方法的有效性.     

Infinite band controller with a fuzzy tuner

Fuzzy logic has been successfully employed in rule-based control systems. In this paper, a fuzzy matrix is used to time an infinite band controller for temperature set point regulation and pressure regulation of an electronics cooling system on Space Station Freedom. The fuzzy tuning matrix shows significant improvement in transient behavior as well as set point tracking. The algorithm was developed in SYSTEM BUILD.     

带积分作用的模糊内模时滞控制器

将Smith预估器和内模控制结构结合起来，使用模糊控制器为主控制器，并用积分环节来消除系统所存在的稳态误差，理论分析可以证明，该结构就是内模控制器，无需滤波环节就可以得到良好的鲁棒性，而模糊控制器本身的非线性和鲁棒性也可以改善系统的动态性能和鲁棒性，经仿真研究发现，只要合理调整模糊比例因子和积分因子，该方法可以在一定的模型失配情况下得到比常规IMC更好的控制品质，且无稳态误差。     

Remotely adjustable robotic grip force for the network-based assembly automation

In the past two decades, robotic assembly has evolved into a part of fully automated, networked production systems that are monitored and controlled from a remotely located central site. Unfortunately, a robotic gripper with a force feedback capability, which can be operated reliably over the Internet under the traffic delay, has not been properly addressed. This study presents a new gripper design of which control model relates the commanded voltage set point in a client computer to the corresponding grip force measured by a server computer. A prototype was developed, and the tests were conducted. The experimental results indicated that the gripper was able to apply and maintain a correct magnitude of grip force according to the types of parts being handled. The feedback control algorithms maintain a grip force at a required level even when the network delay is present. The developed gripper has a great potential for improving the efficiency of the networked, automatic production systems where a frequent changeover is prevalent.     

Linear quadratic optimal controller for cable-driven parallel robots

In recent years, various cable-driven parallel robots have been investigated for their advantages, such as low structural weight, high acceleration, and large workspace, over serial and conventional parallel systems. However, the use of cables lowers the stiffness of these robots, which in turn may decrease motion accuracy. A linear quadratic (LQ) optimal controller can provide all the states of a system for the feedback, such as position and velocity. Thus, the application of such an optimal controller in cable-driven parallel robots can result in more efficient and accurate motion compared to the performance of classical controllers such as the proportional-integral-derivative controller. This paper presents an approach to apply the LQ optimal controller on cable-driven parallel robots. To employ the optimal control theory, the static and dynamic modeling of a 3-DOF planar cable-driven parallel robot (Feriba-3) is developed. The synthesis of the LQ optimal control is described, and the significant experimental results are presented and discussed.     

具有未建模动态机械臂的自适应神经网络控制

对于具有未建模动态机械臂系统,基于神经网络对非线性函数的拟合特性,用径向基神经网络来补偿机械臂系统中的未建模动态,同时提出的自适应神经网络控制器,可以保证具有未建模动态的非线性机械臂系统的渐进稳定特性.仿真结果验证了这种控制策略的有效性.     

盾构掘进偏差模糊控制器的Matlab实现

从盾构掘进的自动控制技术分析,总结了盾构姿态偏差的模糊控制原理.对控制器进行结构设计,然后结合Matlab的模糊控制工具箱中的工具,选取控制器合适的输入和输出变量,利用人工控制的经验并结合专家知识,得出了具有实际意义的盾构模糊控制规则,最后通过Matlab离线计算出模糊控制器的控制表,完成模糊控制器的设计.     

基于模糊控制的电磁式助力转向控制系统

电磁式助力转向是汽车动力转向系统领域的一项新结构。电磁助力器工作电流的控制是电磁式助力控制系统软件设计的一个最基本的控制策略和方法。文中详细地介绍了电磁助力器工作电流模糊控制器的设计方法。文中也给出了方向盘把持力在阶跃输入下的时域响应的仿真结果．该结果表明电磁助力系统具有较好的响应特性。     

A new adaptive controller for constant turning force

A new computerised adaptive control constraint (ACC) system in turning with a constant cutting force constraint is described in this paper. It is shown that the ACC control system based on the fuzzy linguistic rules can achieve an automatic on-line adjustment of feedrate to optimise the production rate even under the variation of cutting conditions in turning operations.     

基于LabVIEW的PID参数自适应模糊控制器设计

PID算法是一个广泛应用于工业控制的算法，但它对非线性和不确定性系统适应性不够理想。PID参数自适应模糊控制器将模糊逻辑推理引入PID参数的在线自调整，是目前一种较为先进的控制器。考虑到LabVIEW是一种基于G语言的高效的专为科学家和工程师设计的虚拟仪器开发工具，这里将Fuzzy Logic Toolkit和PID Controller Toolkit两个工具箱与LabVIEW相结合，实现了上述算法。正是因为LabVIEW能快速构建实现交互控制系统的图形用户界面，并且它与测量、自动化硬件紧密的结合完善了数据采集、信号分析和信息显示的解决方案，这种基于LabVIEW的PID参数自适应模糊控制器在工业控制领域必将有广阔的前景。