一种可演化的查表式模糊逻辑控制器设计与实现

常规的模糊控制器主要通过计算机软件或单片机实现,但模糊控制器是一个高度并行的系统,实时性、自适应性要求较高,这种实现方式不能满足现代模糊控制器的设计要求.要解决这个问题必须从算法和器件结构入手.根据多值逻辑和PLA理论,提出了一种可演化的查表式模糊逻辑控制器.根据模糊逻辑控制器查询表的对称性和单调性特点,提出了一种查询表的简单生成算法.利用J门和PLA设计查询表硬件电路.以典型二阶系统模糊控制为例进行仿真实验,其结果表明了这个可演化的模糊逻辑控制器结构的可行性.     

单片模糊控制器与智PID的实现

模糊逻辑是处理非精确输入与系统非线的强有力处理方法，便于迅速开发鲁棒性控制系统。本文介绍隶属函数、模糊变量、模糊逻辑规则等基本概念，以及单片模糊逻辑控制器的原理与结构，然后以实现智能ＰＩＤ控制为例，系统地叙述了单片模糊逻辑控制器的应用与优点。     

模糊逻辑控制器的演化硬件实现

讨论在演化硬件（EHW）平台上实现模糊逻辑控制器的演化,模糊逻辑控制器是由一些if-the。规则的集合和具有模糊逻辑的输入输出语言术语特点的一些成员属性函数所构成,这里的演化硬件平台是指可编程模拟选择器阵列,通过遗传算法（GA）演化出的电路具有很强的自适应、自修复能力。     

基于LabVIEW的模糊控制器设计与仿真

以LabVIEW编程软件为基础,介绍了其中控制模块中模糊逻辑工具包(Fuzzy LogicToolkit)中的子程序(VI),并应用其中模糊逻辑控制器设计VI构建模糊控制器的方法。设置隶属度函数,建立模糊控制规则,创建模糊推理关系,实现对模糊控制器设计的具体步骤,并结合电液伺服模糊控制系统实例,利用模糊逻辑(Fuzzy logic)模块及LabVIEW提供的仿真模块(Simulation Module)建立系统仿真框图。通过仿真曲线,分析模糊控制器控制效果及其影响因素,从而大大缩短模糊控制器的设计周期,具有较大的工程实用价值。     

单片模糊控制器与智能PID的实现

模糊逻辑是处理非精确输入与非线性的强有力处理方法，便于迅速开发鲁棒性控制系统，本文介绍隶属函数，模糊变量，模糊逻辑规则等基本概念，介绍单片模糊逻辑控制器的原理与结构，最后以实现智能ＰＩＤ控制为例子，系统地叙述了单片模糊逻辑控制器的应用与优点。     

基于模糊控制的某教练机飞行姿态控制器设计

提出了一种基于规则的模糊逻辑飞行控制系统的设计方法,用以解决某教练机训练系统中数学模型时变性和不确定性问题.为了避免建模的困难,某教练机飞控系统采用模糊逻辑控制设计其控制律,结合飞行员的操纵经验,对系统进行动态调整.以俯仰角为研究对象,利用MATLAB中的fuzzy工具箱实现了模糊控制器设计,给出了俯仰角模糊控制器的控制曲面视图,并在SIMULINK仿真环境下建立了仿真模型.结果表明,所设计的模糊逻辑控制器满足操作品质的要求,具有较好的鲁棒性,对教练机驾驶训练仿真平台的飞行控制系统设计具有一定的应用价值.     

一种进化模糊逻辑控制器的新方法

结合进化学习分类器的密歇根和匹兹堡方法的优点,首次将对单条控制规则的评价引入了模糊逻辑控制器（ＦＬＣ）的进化过程中,解决了匹兹堡类型的学习分类器系统“强化信息的带宽窄”的问题,实现了ＦＬＣ在控制器级和规则级的同时进化,控制器的控制规则数目也可以自由变化,实验结果表明新方法有较高的效率,优化的模糊控制器的结构简单,性能良好。     

基于遗传算法和模糊逻辑的智能飞控技术研究

设计了基于遗传算法和模糊逻辑控制的智能飞行控制系统及采用论域自调整的模糊控制器，控制器以角度跟踪误差及其微分信号为输入来控制相应的气动舵面偏转，实现对该姿态的跟踪控制。文中给出了控制器输入输出的隶属函数，设计了相应的规则库。并在此基础上进一步利用遗传算法对模糊控制器进行优化设计，给出了遗传算法各个参数的选择原则。仿真结果表明，基于遗传算法和模糊逻辑的智能飞控系统具有良好的控制效果。     

模糊-PID控制器在空调温度控制中的应用

该文首先利用计算机仿真软件中的优化工具箱对常规PID控制器中的比例、积分和微分参数进行优化，并且针对中央空调温度控制系统非线性、大滞后的特点，设计了在规则上可调整的模糊控制器，该模糊控制器通过α因子自调整和Ku的自寻优，达到适应和跟踪系统参数变化的目的；而后采用模糊逻辑工具箱和MATLAB函数相结合，方便地实现空调温度控制系统的计算机仿真。仿真结果表明，这种控制方式控制效果优于常规PID控制，有效地改善了系统的动态性能、稳态精度和鲁棒性。     

多变量模糊系统控制设计及其在并行混合电动汽车中的应用

利用矩阵半张量积方法研究了多变量模糊系统模糊逻辑控制器的设计,并得到了若干新的结果.首先给出了模糊规则新的表示形式,基于该表示形式,构造了模糊逻辑控制器的结构矩阵,将复杂的模糊推理转变成了简单的代数等式.然后当模糊控制规则不完全时,建立了最小入度控制算法;当模糊控制规则不一致时,给出了相应的处理方法.最后将得到的结果应用到并行混合电动汽车(PHEV)能量管理和控制策略的模糊控制器设计.     

Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers

Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design parameters. The objective is to examine the amount by which the extra degrees of freedom provided by antecedent type-2 fuzzy sets is able to improve the control performance. Experimental results show that better control can be achieved using a type-2 FLC with fewer fuzzy sets/rules so one benefit of type-2 FLC is a lower trade-off between modeling accuracy and interpretability.     

基于GA的模糊控制器在弯辊控制中的应用

UC轧机中间辊弯辊控制回路的数学模型具有很强的时变性和不确定性,为实现其精确控制,设计了一种基于遗传算法的模糊控制器并将其应用于该控制回路中。系统利用遗传算法来优化模糊控制器的隶属函数及量化因子和比例因子的初值,并且根据模糊控制查询表的输出来在线调整量化因子和比例因子。仿真结果表明,用该方法设计的模糊控制器具有一定的自适应能力,将该控制器应用于UC轧机中间辊弯辊控制回路可以使二次型板形缺陷得到快速有效的控制,具有良好的控制性能。     

Position control of electro-hydraulic actuator system using fuzzy logic controller optimized by particle swarm optimization

The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

A Genetic Approach for Simultaneous Design of Membership Functions and Fuzzy Control Rules

Based on the genetic algorithm (GA), an approach is proposed for simultaneous design of membership functions and fuzzy control rules since these two components are interdependent in designing a fuzzy logic controller (FLC). With triangular membership functions, the left and right widths of these functions, the locations of their peaks, and the fuzzy control rules corresponding to every possible combination of input linguistic variables are chosen as parameters to be optimized. By using a proportional scaling method, these parameters are then transformed into real-coded chromosomes, over which the offspring are generated by rank-based reproduction, convex crossover, and nonuniform mutation. Meanwhile, the concept of enlarged sampling space is used to expedite the convergence of the evolutionary process. To show the feasibility and validity of the proposed method, a cart-centering example will be given. The simulation results will show that the designed FLC can drive the cart system from any given initial state to the desired final state even when the cart mass varies within a wide range.     

Control of a distillation column by type-2 and type-1 fuzzy logic PID controllers

The aim of this paper is to develop a type-1 and a type-2 fuzzy logic PID controller (type-1 FLC and type-2 FLC, respectively) for the control of a binary distillation column, the mathematical model of which is characterized by both high nonlinearities and parameter uncertainties. Attention was focused on the tuning procedure proposed by the authors and representing a development of the original Jantzen [1] method for type-1 and type-2 fuzzy controllers, in particular including input type-2 Gaussian membership functions. A theoretical explanation of the differences in fuzzy controller performance was in fact provided in the light of simulation results. The performance of a type-1 FLC was then compared in simulation with the one of type-2 FLC. All the simulation results confirmed the robustness and the effective control action of each fuzzy controller, with evident advantages for the type-2 FLC.