冷连轧模糊反馈AGC系统的设计与仿真

设计了一种模糊控制器，该控制器结构简单，参数调整方便，快捷，将其与PI调节器结合组成智能型复合控制器，并成功应用于冷轧带钢的厚度自动控制（AGC）系统中，仿真实验表明，该控制器的控制性能远优于常规的PID控制器，为冷轧带钢厚度精度的提高提供了一种新的尝试。     

简化的模糊PID控制方案

提出一种简化模糊PID控制方案，将三维的控制规则库简化为二维，大大减少了模糊控制规则的数目，简化了控制策略及控制器的设计和调整过程。并讨论了该控制器的调整方法，最后通过仿真验证了其优越的性能。     

调整系统控制量的模糊PID控制器的计算机设计与仿真

该文提出调整系统控制量的模糊PID控制器的计算机设计与仿真。以碱回收炉的水位控制为例具体论述调整系统控制量的模糊PID控制器的设计、2-D控制表的建立、以及控制器计算机设计与仿真的实现。借助MATLAB模糊控制工具箱和SIMULINK仿真工具进行的仿真实验表明．该控制器既吸收了模糊控制器良好的动态性能．又克服了模糊控制器静态性能较差的缺点。并且为碱回收炉上汽包水位控制提出了一种新的尝试。该控制器结构简单、参数调整方便、快捷。     

基于PLC的模糊PID控制器在发动机试验台测控系统中的应用

将模糊控制和PID控制结合起来运用于发动机试验台测控系统中,构造了一个参数自整定模糊PID控制器,通过模糊控制规则在线调整PID控制器的参数,用MATLAB实现该控制器的仿真。仿真结果表明该控制器的动态响应曲线好、超调量小、稳态精度高。并给出基于PLC直接查表方式实现该模糊PID控制器,为模糊控制技术在工业控制中应用提供了更加广阔的空间。     

一种参数自调整PID模糊控制器

结合传统PID控制原理 ,提出一种新型模糊控制器结构 ,即PID型模糊控制器。为提高PID控制器性能 ,设计能在线调整PID参数的模糊控制方法。仿真结果表明 ,自调整参数PID型模糊控制器使系统在暂态响应及稳态性能方面性能优良。     

参数自调整PID模糊控制器及在数字随动系统中的应用

结合传统PID的控制原理，介绍一种参数自调整的PID模糊控制器。开发了一套能在线调整PID参数的模糊控制方法的软件，并分别将它和传统的PID控制器作用到数字随动系统中。对二者的控制结果进行了比较。实验结果表明，参数自调整PID模糊控制器使系统稳态性能优良，并能提高控制精度。     

一种参数自调整PID模糊控制器

结合传统PID控制原理,提出一种新型模糊控制器结构,即PID模糊控制器。为提高PID控制器性能,设计能在线调整PID参数的模糊控制方法。仿真结果表明,自调整参数PID型模糊控制器使系统在暂态响应及稳态性能方面性能优良。     

三维模糊PID控制器的一种简化

本文提出了一种简化模糊控制方案将三维的控制规则简化为二维控制规则，大大减少了模糊控制规则的数目，简化了控制策略，控制器的设计及调整过程，并讨论了该控制器的调整方法，最后通过仿真验证了其优越性。     

模糊恒压供水系统的设计

本文提出了一种基于模糊控制理论的恒压供水系统，设计出自调整因子控制器，实现了恒压供水，克服了传统PID控制设计中的参数调整困难的问题。介绍了系统的组成及功能。并时系统进行了仿真分析。结果表明，模糊恒压供水系统具有更好的恒压效果。     

基于模糊PID控制在交流伺服系统中的应用

本文采用一种Fuzzy—PID切换型控制器,并将此应用于交流伺服系统的控制中：该控制器具有较完善的控制性能。仿真实验的结果表明,采用该模糊控制的系统能克服传统控制器的弊端,具有较高的稳定精度,较强的鲁棒性。     

一种适用于非最小相位系统的模糊控制方法

针对某一类非最小相位系统的特性,提出一种新型模糊控制器的设计方法,改进了ＰＩＤ型模糊控制器的结构,对输入变量设计了一种简单的可调整宽度的三角形隶属度函数;根据偏差和偏差变化率的相平面图,建立了调节系统的动态特性和规则基之间的定性关系,使规则基的设计趋于简单、合理。水轮机调节系统的仿真结果表明了这种方法的有效性。     

基于PID型模糊神经网络的火电站汽包压力控制

为克服火电站燃料-汽包压力调节对象的非线性、时变和纯迟延特性, 采用含自回归神经元的PID型模糊神经网络作为汽包压力控制器, 进行协调控制系统的设计. 仿真研究表明, 这种初值易选、学习能力较强的模糊神经网络控制器可以克服该对象的时变性和随机性干扰, 大大改善控制品质.     

Optimal PID-type fuzzy logic controller for a multi-input multi-output active magnetic bearing system

The performance of the fuzzy controllers depends highly on the proper selection of some design parameters which is usually tuned iteratively via a trial and error process based primarily on engineering intuition. With the recent developments in the area of global optimization, it has been made possible to obtain the optimal values of the design parameters systematically. Nevertheless, it is well known that unless a priori knowledge is available about the optimization search-domain, most of the available time-domain objective functions may result in undesirable solutions. It is consequently important to provide guidelines on how these parameters affect the closed-loop behavior. As a result, some alternative objective functions are presented for the time-domain optimization of the fuzzy controllers, and the design parameters of a PID-type fuzzy controller are tuned by using the proposed time-domain objective functions. Finally, the real-time application of the optimal PID-type fuzzy controller is investigated on the robust stabilization of a laboratory active magnetic bearing system. The experimental results show that the designed PID-type fuzzy controllers provide much superior performances than the linear on-board controllers while retaining lower profiles of control signals.     

A PLC-based modified-fuzzy controller for PWM-driven induction motor drive with constant V/Hz ratio control

In this paper, a method to develop and design a fuzzy-hybrid control on an industrial controller to control speed of an induction motor and implementing a constant V/Hz ratio control is presented. Detailed discussions on the controller for a PWM-driven induction motor drive system, the system identification for the model transfer function, and the analysis on output responses and the associated manipulated variables are presented. The control objective is to provide an effective control action to sudden changes in reference speed and/or load torque. A switching type controller consisting of two control modes are devised: a PID-type fuzzy controller consisting of a PI-type and a PD-type fuzzy controller, and a conventional PID. At the early phase of the control action, the control task is handled by the PID-type fuzzy controller. At a later phase when the absolute of error is less than a threshold value, the input of integrator at the output side is no longer given by fuzzy action but fed by the incremental PID action. In term of control action, this is an enhanced proportional and derivative action when the actual value is closed to reference. Detailed evaluations of the controller's performance based on pre-defined performance indices under several conditions are presented. The findings demonstrate the ability of the control approach to provide a viable control solution in response to the different operating conditions and requirements.     

PID-type fuzzy logic controller tuning based on particle swarm optimization

In this paper, a new PID-type fuzzy logic controller (FLC) tuning strategy is proposed using a particle swarm optimization (PSO) approach. In order to improve further the performance and robustness properties of the proposed PID-fuzzy approach, two self-tuning mechanisms are introduced. The scaling factors tuning problem of these PID-type FLC structures is formulated and systematically resolved, using a proposed constrained PSO algorithm. The case of an electrical DC drive benchmark is investigated, within a developed real-time framework, to illustrate the efficiency and superiority of the proposed PSO-based fuzzy control approaches. Simulation and experimental results show the advantages of the designed PSO-tuned PID-type FLC structures in terms of efficiency and robustness.     

Intelligent transportation control system design using wavelet neural network and PID-type learning algorithms

In this paper, an intelligent transportation control system (ITCS) using wavelet neural network (WNN) and proportional-integral-derivative-type (PID-type) learning algorithms is developed to increase the safety and efficiency in transportation process. The proposed control system is composed of a neural controller and an auxiliary compensation controller. The neural controller acts as the main tracking controller, which is designed via a WNN to mimic the merits of an ideal total sliding-mode control (TSMC) law. The PID-type learning algorithms are derived from the Lyapunov stability theorem, which are utilized to adjust the parameters of WNN on-line for further assuring system stability and obtaining a fast convergence. Moreover, based on H_∞ control technique, the auxiliary compensation controller is developed to attenuate the effect of the approximation error between WNN and ideal TSMC law, so that the desired attenuation level can be achieved. Finally, to investigate the effectiveness of the proposed control strategy, it is applied to control a marine transportation system and a land transportation system. The simulation results demonstrate that the proposed WNN-based ITCS with PID-type learning algorithms can achieve favorable control performance than other control methods.     

Neural network based adaptive fuzzy PID-type sliding mode attitude control for a reentry vehicle

This work investigates the attitude control of reentry vehicle under modeling inaccuracies and external disturbances. A robust adaptive fuzzy PID-type sliding mode control (AFPID-SMC) is designed with the utilization of radial basis function (RBF) neural network. In order to improve the transient performance and ensure small steady state tracking error, the gain parameters of PID-type sliding mode manifold are adjusted online by using adaptive fuzzy logic system (FLS). Additionally, the designed new adaptive law can ensure that the closed-loop system is asymptotically stable. Meanwhile, the problem of the actuator saturation, caused by integral term of sliding mode manifold, is avoided even under large initial tracking error. Furthermore, to eliminate the need of a priori knowledge of the disturbance upper bound, RBF neural network observer is used to estimate the disturbance information. The stability of the closed-loop system is proved via Lyapunov direct approach. Finally, the numerical simulations verify that the proposed controller is better than conventional PID-type SMC in terms of improving the transient performance and robustness.

     

开关电源模糊控制PID的设计和MATLAB仿真研究

本文提出了一种开关电源模糊控制PID的的设计和MATLAB仿真方法。仿真结果表明:具有模糊控制的PID动态响应快、超调量小、负载变化引起输出电压的变化小。