基于模糊推理的自整定PID控制器

本文提出一种基于模糊推理的自整定PID控制器，利用模糊推理来优化PID控制器参数。文章深入介绍了以80C196KC单片机为核心的自整定PID控制器的软、硬件电路设计及实现。     

A fuzzy PID controller for nonlinear and uncertain systems

 In order to control systems that contain nonlinearities or uncertainties, control strategies must deal with the effects of these. Since most control methods based on mathematical models have been mainly focused on stability robustness against nonlinearities or uncertainties, they are limited in their ability to improve the transient responses. In this paper, a nonlinear fuzzy PID control method is suggested, which can stably improve the transient responses of systems disturbed by nonlinearities or unknown mathematical characteristics. Although the derivation of the control law is based on the design procedure for general fuzzy logic controllers, the resultant control algorithm has analytical form with time varying PID gains rather than linguistic form. This means the implementation of the proposed method can be easily and effectively applied to real-time control situations. Control simulations are carried out to evaluate the transient performance of the suggested method through example systems, by comparing its responses with those of the nonlinear fuzzy PI control method developed in [9].     

一种PID模糊控制器(fuzzy PI+fuzzy ID型)

提出一种二维PID模糊控制器,其结构形式筒称为fuzzy PI+fuzzy ID型.根据fuzzy PI和fuzzy ID控制器的图解说明,确定该fuzzy PI和fuzzy ID控制器的模糊控制规则的相似性.理论分析表明,该PID模糊控制器除具有常规PID性能外,还具有非线性等特点.仿真结果表明,与常规PID和fuzzy PI控制相比性能更优.     

A novel design of high-sensitive fuzzy PID controller

A hybrid model is designed by combining the genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic to determine the optimal parameters of a proportional-integral-derivative (PID) controller. Our approach used the rule base of the Sugeno fuzzy system and fuzzy PID controller of the automatic voltage regulator (AVR) to improve the system sensitive response. The rule base is developed by proposing a feature extraction for genetic neural fuzzy PID controller through integrating the GA with radial basis function neural network. The GNFPID controller is found to possess excellent features of easy implementation, stable convergence characteristic, good computational efficiency and high-quality solution. Our simulation provides high sensitive response (∼0.005 s) of an AVR system compared to the real-code genetic algorithm (RGA), a linear-quadratic regulator (LQR) method and GA. We assert that GNFPID is highly efficient and robust in improving the sensitive response of an AVR system.     

间歇精馏过程的模糊逻辑与增益自调整PID混合控制

针对间歇精馏过程的强非线性和非平稳时变特性,结合模糊逻辑控制和增益自调整PID控制的优点,提出了一种模糊逻辑和增益自调整PID混合控制的先进控制策略,详细推导了其控制算法,设计了相应的控制器,并在EuroBEEB工控机上用实时BASIC语言编程实现,对一套甲醇/水二元间歇精馏塔的塔顶浓度进行了推断控制实验,获得了比单独采用模糊逻辑控制时更好的控制结果。这说明,模糊逻辑和增益自调整PID混合控制是强非线性和非平稳时变过程的一种有效控制策略。     

模糊自整定PID控制器在再热汽温控制中的应用研究

针对工业过程中再热汽温等一类大迟延惯性时变对象,采用模糊自整定PID控制器对PID参数调节和优化,该方法将模糊技术与PID控制综合起来,实现了PID控制的智能化。仿真结果表明:与常规PID控制器相比,模糊自整定PID控制器具有很强的适应性、鲁棒性和抗干扰性。     

基于模糊PID的静变电源控制技术研究

为提高静变电源输出电压的质量,研究了一种自整定模糊PID控制方法。该方法将模糊控制优良的动态性能、灵活的控制特性和PID稳态控制性能的优势相结合,实时地对系统控制量进行调整。在Matlab/Simulink环境下,对于模糊PID和常规PID在静变电源控制中的应用分别进行了仿真。仿真结果表明,模糊PID控制器减少了超调量,抗干扰性和鲁棒性强,系统的动态、稳态性能得到了很大程度的提高。     

一种基于模糊逻辑的入口匝道自适应控制器

高速公路的交通流存在很大的不确定性,模糊逻辑是解决其控制问题的有效方法。对传统的ALINEA模型进行了扩展,提出一种新的自适应模糊匝道控制器。当高速公路路段的临界密度不能被预先正确估计或者因交通环境的实时变化而难以估计时,提出的自适应模糊控制器将显示出其优越性。在仿真试验中,根据交通流的各种性能指标,将新的自适应控制器同传统的ALINEA方法做了详细的对比。     

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.     

Systematic design of a stable type-2 fuzzy logic controller

Stability is one of the more important aspects in the traditional knowledge of automatic control. Type-2 fuzzy logic is an emerging and promising area for achieving intelligent control (in this case, fuzzy control). In this work we use the fuzzy Lyapunov synthesis as proposed by Margaliot and Langholz [M. Margaliot, G. Langholz, New Approaches to Fuzzy Modeling and Control: Design and Analysis, World Scientific, Singapore, 2000] to build a Lyapunov stable type-1 fuzzy logic control system, and then we make an extension from a type-1 to a type-2 fuzzy logic control system, ensuring the stability on the control system and proving the robustness of the corresponding fuzzy controller.     

分数阶模糊免疫PID控制器的设计

为改善分数阶PID控制器的控制性能,借鉴整数阶模糊免疫PID控制器,把模糊免疫调节与分数阶PID控制器结合起来,设计了分数阶模糊免疫PID控制器。仿真结果表明了该方法的有效性,不但提高了分数阶PID控制器跟踪性能,而且还具有良好的鲁棒性和抗干扰性。     

双闭环直流调速系统模糊PID控制研究*

针对电压和负载扰动导致传统PID控制双闭环直流调速系统性能下降的问题,本文提出一种模糊PID控制方法。本文的控制方法根据调速系统的转速偏差e和偏差变化率ec,经过模糊逻辑推理,动态自适应调整PID控制器的三个参数,能够有效提高系统抗扰动能力。为了对两种控制方法的性能进行比较分析,文中对系统在理想空载状态、负载扰动和电压波动三种情况下进行仿真试验。结果表明两种控制方法在理想空载状态下的稳态性能基本相同。在负载扰动和电压波动的情况下,本文的方法能使系统更快恢复到平衡状态,且具有更小的转速降。因此,本文的控制方法能够保证系统具有较好的动态性能和抗扰性能。     

一种改进的区间二型模糊控制器设计

针对二型模糊控制器设计中出现的降型计算方法损失不确定性信息的问题,提出一种改进的区间二型模糊控制器．该控制器在充分利用二型模糊推理结果的前提下,对区间模糊输出进行再次优化,其优化指标可直接与被控系统性能相关,由此可得到更有利于提高系统整体性能的准确输出量．最后,将改进的控制器用于汽车非线性悬架系统的控制,仿真结果验证了所提出方法的有效性．     

A fuzzy expert system shell using both exact and inexact reasoning

This paper presents a comprehensive expert system shell which can deal with both exact and inexact reasoning. A prototype of this proposed shell, code named as SYSTEM Z-IIe, has been implemented successfully. It is a rule-based system which employs fuzzy logic and numbers for its reasoning. Two basic inexact concepts, fuzziness and uncertainty, are both used and distinct from each other clearly in the system. Moreover, these two concepts have been built into two levels for inexact reasoning, i.e. the level of the rules and facts, and the level of the values of the objects of these rules and facts. Other features of Z-IIe include multiple fuzzy propositions in rules and dual fact input mechanisms. It also allows any combinations of fuzzy and normal terms and uncertainties. Fuzzy numeric comparison logic control is also available for the rules and facts. Its natural language interface which uses English with restricted syntax improves the efficiency of knowledge engineering. Z-IIe is also coupled to a Database Management System for supplying facts from existing databases if appropriate. All these features can be combined to build very powerful expert systems and are illustrated by an example.     

模糊逻辑在PID参数整定中的应用

PID控制是最早发展起来的控制策略之一,由于受到参数整定方法烦杂的困扰,常规PID控制器参数往往性能欠佳,对运行工作情况的适应性差。本设计将模糊控制和PID控制结合起来,构建自适应模糊PID控制器,实现PID参数的最佳调整。该模糊自整定PID控制器既具有PID控制器高精度的优点,又具有模糊控制器快速、稳态特性。     

Theoretical and linguistic aspects of the fuzzy logic controller

Successful applications of the fuzzy logic controller by various researchers to a variety of ill-defined processes motivated this theoretical study of the fuzzy logic controller. Initially the controller is analysed by traditional (nonlinear) algebraic methods which are particularly useful in stability studies, provided the process is algebraically modelled. Despite the success of this technique, it suffers from a major limitation in that the algebraic model of the controller cannot directly deal with the linguistic aspects of the fuzzy logic controller. This observation leads to the introduction of a more concise, and hence more powerful, notation for representing the linguistic rules that describe the fuzzy logic controller. The so-called linguistic models that arise from this notation are shown to be extremely useful for modelling highly nonlinear low-order systems and for determining, explicitly, the rules of ‘optimal’ fuzzy logic controllers.     

Improving performance of switched reluctance motor by fuzzy logic controller

This paper presents torque ripple minimization of a switched reluctance motor (SRM) by using a fuzzy controller. The nonlinear model of the SRM and the mathematical model of the converter circuit are driven. The motor used in both simulation and experiment is an 8/6 four phase SRM with a C-Dump converter. The applied fuzzy controller adjusts the value of the reference current to keep the speed of the motor constant. The results show that the fuzzy logic is effective in reducing the torque ripple of the motor, and compensating for the nonlinear torque characteristics. The experimental result is given for a current control algorithm, and it shows that the quite nonlinear model of the SRM is well defined. Copyright © 1999 John Wiley & Sons, Ltd.     

气动位置伺服系统的非对称模糊PID控制

对于有杆气缸的非对称物理及摩擦力特性,提出了采用非对称模糊策略的模糊PID控制算法,较好地解决了有杆气缸由于左右两腔物理结构和摩擦力特性的不对称而造成运动过程中压力变化复杂的问题,改善了系统的动态响应性能.实验证明,采用非对称模糊策略的模糊PID控制可以明显地提高气动位置伺服系统的动态响应性能,系统具有较小的超调量和过渡过程时间,并获得了满意的重复稳态精度.     

A general approach to rule aggregation in fuzzy logic control

We look at the representation and aggregation of individual rules in the fuzzy logic control system. Two extreme paradigms for rule representation are introduced, the Mamdani model and the logical model. We look at the characteristics of these approaches. We then combine these two approaches to get a general model for the representation of rules. From this general formulation we obtain two soft classes of rules aggregation, or-like and and-like aggregations.     

基于TS模型的增益自校正单神经元PID控制算法

将单神经元自适应PID控制算法和基于TS模型的模糊推理系统相结合,提出了增益模糊自校正单神经元PID控制算法。该算法使得传统单神经元自适应PID控制的神经元增益具备在线自动调整的功能,对于变增益的不确定性系统的控制,获得了很好的控制性能。