一种采用自适应遗传算法的模糊自整定控制器

针对模糊自整定控制器参数寻优能力差的不足,研究了采用自适应交叉概率与变异概率的遗传算法,提出了用这种自适应遗传算法改善模糊自整定控制器性能的方法。对采用自适应遗传算法的模糊自整定控制器与一般的模糊自适应控制器作了仿真对比研究,说明了前者的优越性。     

一种控制规则自调整的模糊控制器

根据模糊控制理论和实际工程经验，设计了一个控制规则能够自调整的模糊控制器，详细介绍了该模糊控制器的控制原理和运行机制，并作出了仿真。该模糊控制器控制精度高，动态和稳态性能均优于传统的PID和基本模糊控制器，且具有较好的鲁棒性和抗扰动能力。仿真和工程实践证明，该模糊控制器具有简便、稳定的优点，且易于工程实现，具有较高的工程应用价值。     

一种汽车主动悬架系统模糊控制器设计及试验

设计了一种在线可调整的模糊控制器，其模糊控制规则表可以用解析的方法进行计算。不仅体现了模糊控制算法对非线性系统具有的明显优势，而且利用LMS自适应模块调整模糊控制器的修正因子，改善单一模糊控制算法对专家先期经验的依赖缺陷。针对简化的汽车模型，在以单频信号作为激励源的仿真研究过程中，该算法对悬架系统的振动控制收到了较好的效果。在两自由度的悬架系统试验台架上进行了试验研究，结果进一步证明该算法的有效性。     

一种模糊自适应控制器

本文提出了一种根据系统输入一输出数据在线改模糊关系的模糊自适应控制器。文中给出一个由不稳定非最小相位线性部分和饱和非线性两部分组成的随机系统仿真示例，仿真结果表明该控制器有效的。     

浅谈模糊控制器的基本工作原理

模糊控制是建立在模糊推理基础上的一种非线性控制策略。它通过模糊语言表达了人们的操作经验以及常识推理规则。采用这种控制策略的控制器就叫模糊控制器,它是一种语言型控制器。模糊控制器是以模糊集理论为基础发展起来的,并已成为把人的控制经验及推理纳人自动控制策略之中的一条简洁的途径。     

一种改进的模糊神经网络控制器学习算法

提出了一种改进的模糊神经网络混合学习算法,运用遗传算法优化构成隶属函数的网络结构,运用最小二乘法进行解模糊,具有更高的学习精度和更快的收敛速度,解决了在多变量系统中采用模糊神经网络时学习收敛慢且易陷入局部极小点的问题。     

一种模糊Rough决策方法

利用模糊集理论和粗糙集理论在处理不确定性和不精确性问题方面侧重点的差异性，构造一种组合决策模型。该模型从问题领域内的部分不精确信息出发利用模糊聚类方法构造一个决策信息系统，利用粗糙集理论关于决策规则的约简方法从决策信息系统中提取（挖掘）决策规则，使之适用于问题的整个领域。     

一种运用遗传算法确定船舶航向控制模糊规则的方法

为了克服船舶航向控制模糊规则确定过程中的盲目性，引入一种与之相适应的遗传算法，以使结果成为某种意义下的最优解，从而从根本上解决这一重要问题．文中运用Matlab的C语言MEX—文件技术，将遗传算法源代码与Matlab直接结合起来，利用后者的强大建模能力，建立起完整的仿真模型．仿真结果表明，船舶的航向控制能力得到明显改善．     

一种模糊自适应PID控制器的设计与仿真

介绍一种基于模糊控制原理的自适应PID控制方法,实现PID控制器参数的在线自调整.仿真实验结果表明,此方法具有良好的动态、静态特性和较强的鲁棒性.     

Linear defuzzified output of fuzzy controllers via mixed fuzzy logic operators

Abstract

The linear defuzzified output of a fuzzy controller with two fuzzy variable inputs and one output is discussed in this paper. Arbitrary amounts of triangular fuzzy numbers are employed to fuzzify the linguistic variables in fuzzy control rules. We show that the defuzzified output is exactly equivalent to a linear function of the inputs to the fuzzy controller by using three mixed fuzzy logic operators to evaluate the control rules.     

Speed control of SR motor by self-tuning fuzzy PI controller with artificial neural network

In this work, the dynamic model, flux-current-rotor position and torque-current-rotor position values of the switched reluctance motor (SRM) are obtained in MATLAB/Simulink. Motor control speed is achieved by self-tuning fuzzy PI (Proportional Integral) controller with artificial neural network tuning (NSTFPI). Performance of NSTFPI controller is compared with performance of fuzzy logic (FL) and fuzzy logic PI (FLPI) controllers in respect of rise time, settling time, overshoot and steady state error.     

Designing a belt conveyor controller in a bottling plant using fuzzy logic and genetic algorithms

This paper presents an industrial case study relevant to a fuzzy logic controller designed via a properly developed genetic algorithm. We consider an example of a fuzzy logic‐based industrial process‐controller. In particular, we deal with the problem of controlling the speed of a belt conveyor for glass containers in a bottling plant. The primary objective of the controller is to guarantee the continuous feed to the filling station, in the presence of frequent gaps between bottles. The secondary objective is to reduce the impact speed between arriving bottles and those standing in the queue, in order to reduce the plant noise. High‐performance parameters of the fuzzy controller are found by a properly developed genetic algorithm. The results provided by Monte Carlo simulations demonstrate that, with such controllers, it is possible to achieve both the objectives mentioned above. Copyright © 2001 John Wiley & Sons, Ltd.     

基于带修正因子的模糊控制汽车主动悬架系统的研究

根据路面 -汽车系统的特点 ,提出一种在线可调整的模糊控制算法 ,其模糊控制规则表可以用解析的方法进行计算。该方法不仅体现了模糊控制算法对非线性系统具有的明显优势 ,而且利用 L MS自适应模块调整模糊控制器的修正因子 ,改善单一模糊控制算法对专家先期经验的依赖缺陷。针对简化的汽车模型 ,以汽车操纵稳定性及行驶平顺性为控制目标 ,进行了仿真计算及分析。又进一步在两自由度系统上进行了台架试验研究 ,结果证明该算法对系统的振动控制具有较好的效果。     

Novel type-2 fuzzy logic technique for handover problems in a heterogeneous network

Small cells are deployed in the long-term evolution—advanced (LTE-A) data standard to satisfy rapidly increasing data rates at hotspots and enhance coverage in buildings. Small cells are low-cost, low-power nodes with limited coverage. With small cells, the more sophisticated network architecture increases the difficulty of dealing with mobility management. The conflict between traffic demands and network resources is also very important, and the signalling overhead (ping-pong) in the handover procedure should be considered in mobility management. With the aim of solving these issues, efficient handover algorithms are being used to enhance mobility management in small-cell networks. This article presents a new handover optimization algorithm for LTE-A networks based on fuzzy logic. It consists of selecting the optimum handover margins for both macro and small cells which are required for the handover process to optimize the performance metrics. The proposed handover optimization technique is evaluated and compared with two well-known handover algorithms. The results show that it achieves a minimum call drop rate and has a minimum number of handovers.     

An approach of fuzzy logic evaluation and control in SPC

Quality control plays an important part in most industrial systems. Its role in providing relevant and timely data to management for decision‐making purposes is vital. A method that uses statistical techniques to monitor and control product quality is called statistical process control (SPC), where control charts are test tools frequently used for monitoring the manufacturing process. Engineers or managers can evaluate an abnormal process by using SPC zone rules in control charts. In the conventional use of the zone rules the user is only able to determine whether or not the process is out of control. What action should be taken to adjust the process is uncertain and is evaluated based on knowledge of the system and past experiences. This paper explores the integration of fuzzy logic and control charts to create and design a fuzzy–SPC evaluation and control (FSEC) method based on the application of fuzzy logic to the SPC zone rules. A simulation program implementing FSEC was written in Borland C++ 5.0 and simulation results were obtained and analysed. The abnormal processes simulated were automatically adjusted for each of the zone rules tested and showed an improved performance after the control action, thus confirming the merit of the technique as a special method with the specific numerical control action based on a quality evaluation criterion. Copyright © 2000 John Wiley & Sons, Ltd.     

Fuzzy logic controller in a packaging plant

This paper deals with the analysis of a controller used to synchronize two parallel belt conveyors in a packaging plant. A first conveyor carries the products, while the second delivers the packages. The insertion is obtained by a proper mechanical action. The control system is based on a ‘hybrid’ fuzzy logic controller, whose parameters are optimized by using an advanced ‘operational’ genetic algorithm. ‘Hybrid’ means that a conventional fuzzy logic controller is integrated with a set of special rules needed to solve particular situations characterizing the system. An important constraint is given, since the physical structure of the existing control system is to be kept unchanged. It is shown that the controller efficiently governs the belt conveyors when: (a) the distances between goods and the relative packages become higher than a certain value; (b) the performance of the electrical engine deteriorates during working time; and also (c) interference phenomena occur between consecutive good‐package couples. Copyright ©2003 John Wiley & Sons, Ltd.     

Different control applications on a vehicle using fuzzy logic control

In this paper, the active suspension control of a vehicle model that has five degrees of freedom with a passenger seat using a fuzzy logic controller is studied. Three cases are taken into account as different control applications. In the first case, the vehicle model having passive suspensions with an active passenger seat is controlled. In the second case, active suspensions with passive passenger seat combination are controlled. In the third case, both the passenger seat and suspensions have active controllers. Vibrations of the passenger seat in the three cases due to road bump input are simulated. At the end of the study, the results are compared in order to select the combination that supplies the best ride comfort.     

Evaluation of leagility in supply chains using fuzzy logic approach

In the changing business environment, manufacturing firms can survive by catering to the dynamic demands of the modern customers. Lean principles imply zero inventory and agile principles necessitate safety inventory to tackle volatile market conditions. The leagile paradigm is gaining importance in the contemporary scenario which includes both lean and agile principles. This article presents the conceptual model of leagility imbibed with lean and agile principles. A fuzzy logic approach has been used for the evaluation of leagility in supply chains. This article is used to compute the performance of supply chains using both lean and agile concepts as leagility supply chains using a fuzzy logic approach.