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。     

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。     

基于跟踪误差调节的非线性自适应模糊预测控制

将模糊逻辑系统引入预测控制,对一类非线性离散系统提出了直接自适应模糊预测控制的方法,此方法首先建立被控对象的预测模型;然后基于此模型直接利用模糊逻辑系统设计预测控制器,并基于跟踪误差对控制器参数中的未知向量进行自适应调整;最后证明了此方法可使跟踪误差收敛到原点的一个小邻域内。     

模糊逻辑系统设计分析

模糊逻辑是以模糊理论为基础，允许用语言和了表示操作和控制规律。实际它比数学方法更好，用直观方法代替复杂数学模型。我们提出一简单模糊系统，说明如何将模糊逻辑引入到该系统中。范例概念直接了当，论文目的不在于设计一个交通灯，而在于说明如何设计一个模糊系统。     

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     

Genetic algorithm design of neural network and fuzzy logic controllers

This paper discusses the design of neural network and fuzzy logic controllers using genetic algorithms, for real-time control of flows in sewerage networks. The soft controllers operate in a critical control range, with a simple set-point strategy governing “easy” cases. The genetic algorithm designs controllers and set-points by repeated application of a simulator. A comparison between neural network, fuzzy logic and benchmark controller performance is presented. Global and local control strategies are compared. Methods to reduce execution time of the genetic algorithm, including the use of a Tabu algorithm for training data selection, are also discussed. The results indicate that local control is superior to global control, and that the genetic algorithm design of soft controllers is feasible even for complex flow systems of a realistic scale. Neural network and fuzzy logic controllers have comparable performance, although neural networks can be successfully optimised more consistently.     

Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic

Uncertainty is an inherent part in control systems used in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional fuzzy systems cannot fully handle the uncertainties present in control systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us with more parameters and more design degrees of freedom. This paper deals with the design of control systems using type-2 fuzzy logic for minimizing the effects of uncertainty produced by the instrumentation elements, environmental noise, etc. The experimental results are divided in two classes, in the first class, simulations of a feedback control system for a non-linear plant using type-1 and type-2 fuzzy logic controllers are presented; a comparative analysis of the systems’ response in both cases was performed, with and without the presence of uncertainty. For the second class, a non-linear identification problem for time-series prediction is presented. Based on the experimental results the conclusion is that the best results are obtained using type-2 fuzzy systems.     

Adaptive sliding mode control for MIMO nonlinear systems based on fuzzy logic scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.     

一类未知非线性离散系统的直接自适应模糊预测控制

将自适应模糊逻辑系统引入预测控制,对一类未知非线性离散系统提出了直接自适应模糊预测控制方法.首先对被控对象提出了线性时变子模型加非线性子模型的预测模型,然后直接利用模糊逻辑系统设计预测控制器,并基于广义误差估计值对控制器参数和广义误差估计值中的未知向量进行自适应调整.文中证明了此方法可使广义误差估计值收敛到原点的小邻域内.     

Fuzzy adaptive output feedback control for a class of switched non-triangular structure nonlinear systems with time-varying delays

This paper investigates an adaptive fuzzy output feedback control design problem for switched nonlinear system in non-triangular structure form. The discussed system contains unknown nonlinear dynamics, unmeasured states and unknown time-varying delays under a batch of switching signals. Fuzzy logic systems are utilised to learn unknown nonlinear dynamics and construct a fuzzy switched nonlinear observer. By combining the property of fuzzy basis function with Lyapunov–Krasovskii functional and the command filter, a novel observer-based fuzzy adaptive backstepping schematic design algorithm is presented. Furthermore, the stability of the closed-loop control system is proved via Lyapunov stability theory and average dwell time method. The simulation results are presented to verify the validity of the proposed control scheme.     

自适应模糊PID控制器的设计

目前的工业过程控制中被控对象往往都是非线性、时变的系统,常规PID控制对于这样系统的控制效果不是很理想。为此,提出将模糊技术与PID控制相结合的控制方式,设计出自适应模糊PID控制器。利用Matlab中模糊逻辑控制工具箱设计模糊控制器,在Simulink环境中实现了该自适应模糊PID控制器的仿真。仿真结果表明,该模糊PID控制具有控制灵活、响应快和适应性能强的优点。     

基于MATLAB环境下模糊控制参数的优化设计与仿真

该文提出了一种基于MATLAB环境下，利用优化工具箱和模糊逻辑工具箱以及M函数文件，使用单纯形法对模糊控制器中的量化因子和比例因子进行自寻优，可获得一个基于一定性能指标的次优或最优模糊控制器。以二阶系统为例进行了计算机仿真，仿真结果表明该方法具有良好的收敛性，使系统的动态性能得到明显的改善。     

Some implications of fuzzy set theory applied to geographic databases

Present geographic database design is based on Boolean logic. The inadequacy of this logic for representation and manipulation of inexact data has recently become a major topic of debate. This is a first attempt at formulating a consistent model for handling inexactness in geographic information systems by introducing a logic of inexactness. Fuzzy logic serves as the basis for representing and manipulating inexactness in a relational geographic database. Four distinct cases of nonfuzzy schema/nonfuzzy data, nonfuzzy schema/fuzzy data, fuzzy schema/ nonfuzzy data, and fuzzy schema/fuzzy data are presented. Two models of managing fuzzy data within a nonfuzzy schema are presented.     

Intuit before tuning: Type-1 and type-2 fuzzy logic controllers

Although a considerable amount of effort has been put in to show that fuzzy logic controllers have exceptional capabilities of dealing with uncertainty, there are still noteworthy concerns, e.g., the design of fuzzy logic controllers is an arduous task due to the lack of closed-form input–output relationships which is a limitation to interpretability of these controllers. The role of design parameters in fuzzy logic controllers, such as position, shape, and height of membership functions, is not straightforward. Motivated by the fact that the availability of an interpretable relationship from input to output will simplify the design procedure of fuzzy logic controllers, the main aims in this work are derive fuzzy mappings for both type-1 and interval type-2 fuzzy logic controllers, analyse them, and eventually benefit from such a nonlinear mapping to design fuzzy logic controllers. Thereafter, simulation and real-time experimental results support the presented theoretical findings.     

一类严格反馈系统变比例增益精确微分补偿控制

针对包含不确定函数和未知外部扰动的一类严格反馈型非线性系统,提出基于精确扰动观测器的变比例增益自适应模糊控制器.系统中的未知不确定函数由模糊逻辑系统在线逼近,同时将模糊逻辑系统的逼近误差和未知外部扰动定义为总扰动,利用精确扰动观测器进行精确微分补偿控制. 将非线性函数应用于设计可调节的输出反馈增益,有效消除系统的稳态误差,使得系统跟踪误差可以控制在零的任意小邻域内.最后,通过Lyapunov定理证明闭环系统中所有信号均是有界的.数值仿真表明了所提出方案的有效性.     

Fuzzy control of a mobile robot

This paper describes the design of a new fuzzy logic-based navigation algorithm for autonomous robots. This design effectively achieves correct environment modeling and noisy and uncertain sensory data processing on low-cost hardware equipment. A hierarchical control strategy is presented in which three different reactive behaviors are fused in a single control law by means of a fuzzy supervisor guaranteeing robot safety and task accomplishment. Due to the inherent transparency of fuzzy logic, the proposed algorithm is computationally light, easily reconfigurable, and well-performing in a wide range of differing operating conditions and environments     

最优模糊控制器的系统设计

典型模糊控制器在难于建立数学模型或对控制精度要求不高的场合已得到了成功的应用，但与传统的控制方法相比，它存在两个明显的弱点，一个所得到的模糊控制规则不能保证其是优的或是次最优的，二是在设计模糊控制器获取模糊控制规则时主要是凭经验进行，没有的步骤可遵循，本文提出了一类最优模糊控制器的系统设计方法及步骤，这种最优模糊控制器既有典型模糊控制器的形式，又有类似于线性二次型的性能指标Ｊ＝ｒｆ∑ｋ＝１（ａＮＡ     

Single-chip fuzzy logic controller design and an application on a permanent magnet dc motor

This paper describes a low-cost single-chip PI-type fuzzy logic controller design and an application on a permanent magnet dc motor drive. The presented controller application calculates the duty cycle of the PWM chopper drive and can be used to dc–dc converters as well. The self-tuning capability makes the controller robust and all the tasks are carried out by a single chip reducing the cost of the system and so program code optimization is achieved. A simple, but effective algorithm is developed to calculate numerical values instead of linguistic rules. In this way, external memory usage is eliminated. The contribution of this paper is to present the feasibility of a high-performance non-linear fuzzy logic controller which can be implemented by using a general purpose microcontroller without modified fuzzy methods. The developed fuzzy logic controller was simulated in MATLAB/SIMULINK. The theoretical and experimental results indicate that the implemented fuzzy logic controller has a high performance for real-time control over a wide range of operating conditions.     

一类多变量非线性动态系统的鲁棒自适应模糊控制

对一类非线性多变量未知动态系统,提出了一种自适应模糊控制策略.策略中采用IF-THEN推理规则来构造模糊逻辑系统,实现对系统中未知函数的估计,在建模误差为零的条件下设计状态反馈控制器及参数的自适应律.分析了当存在建模误差时,闭环系统的稳定性和鲁棒性.     

模糊相容图

本文提出了模糊开关函数极小化的新方法,建立了一种模糊相容图,用它求函数的极小覆盖,既不用模糊本原蕴含总集,也不要分解短语,可有效地用于多变量函数的模糊逻辑开关系统或连续逻辑开关系统的设计.