一种基于Labwindows和Matlab的模糊自适应PID控制器设计

PID控制是一个广泛应用于工业控制的算法,但它对非线性和不确定性系统适应性不够理想。PID参数自适应模糊控制器将模糊逻辑推理引入PID参数的在线自调整,是目前一种较为先进的控制器。本文介绍了模糊自整定PID控制器的设计方法,利用Matlab中的模糊工具箱设计模糊控制器,将PID与模糊控制器有机结合,并引入Labwindows虚拟仪器平台,实现PID参数自调整模糊控制系统的设计和仿真。结果表明,该控制器改善了控制系统的动态性能,增强了其实用性。     

一种解析的模糊PI自整定方法

针对模糊PID控制器缺乏系统的整定方法的问题,提出了一种解析的基于增益裕度和相位裕度的模糊PI控制器的参数自整定方法。首先推导出模糊PI控制器的解析模型,该解析模型包括线性控制器和非线性补偿控制器2个部分。参数整定时,将非线性补偿控制器看作过程的扰动,由线性控制器和被控对象的一阶纯时滞模型,基于系统的增益裕度和相位裕度,导出模糊PI控制器的参数。仿真结果表明,对于时变高阶系统,和传统的PI控制器相比,模糊PI控制器具有鲁棒性强,超调小,调整时间短等优点。     

回转窑煅烧带温度控制器的设计与仿真

针对传统的回转窑煅烧带温度PID控制系统存在温度稳定性差、无法在线调整PID参数等问题,文章提出了一种采用模糊自整定PID参数控制方式设计回转窑煅烧带温度控制器的方案,介绍了该控制器的结构、设计步骤及回转窑煅烧过程系统的建模等,并采用Matlab中的Simulink模糊工具箱对模糊自整定PID温度控制器进行了仿真。仿真结果表明,该控制方法无超调量、调节时间短,能够实现参数的在线自调整。实际应用也证明了该控制方法的优越性。     

基于倒立摆的一种控制器的设计与仿真

针对倒立摆多输入多输出系统，由于复杂非线性，强耦合性而难以建立数学模型和难以控制的问题．提出一种PID参数模糊自整定的控制方法。利用MATLAB设计PID参数模糊自整定控制器，并进行仿真和实际应用。通过与常规PID控制方法相比较，可以看出PID参数模糊自整定的控制方法不需要建立精确的数学模型，还可以及时在线调整PID参数，获得更好的控制效果。     

基于增益调整型模糊PID的脉动真空灭菌器控制系统

针对目前脉动真空灭菌器控制效果不好而产生湿包的问题,结合Chien-Hrones-Reswicks整定算法,提出用模糊变增益PID的控制策略,控制器输入取控制舱内温度的偏差e和偏差变化率△e;根据实际操作经验,加入模糊规则,输出取PID控制器2个参数的调整值,从而实现PID参数的在线自整定;在MATLAB/SIMULINK环境下进行了仿真实验,进行了传统PID控制与模糊变增益PID控制动态性能的仿真比较,结果表明采用模糊变增益PID控制策略可明显提高脉动真空灭菌控制系统的动态性能.     

模糊增益调整PID控制在VAV系统中的应用

本文针对用普通PID控制对VAV系统控制参数难以整定的问题,设计了一种基于模糊控制原理的PID参数在线自调整控制器,根据偏差和偏差变化率来实时调整KP,Ki,Kd参数。通过计算机仿真结果表明,这种模糊增益调整PID控制器比常规PID控制器有更好的控制效果,大大改善了系统的动态和稳态性能。     

时滞系统模糊整定PID控制的仿真研究

文中引入1／1pade级数逼近纯滞后环节，根据两步法设计内模控制器。由等效式可以看出，单位反馈控制器可以由带滤波器的PID控制器文现，内模调节即转化成为PID控制器的参数整定。采用模糊自调整控制方案整定PID参数，同时结合针对时滞系统的模糊控制规则和一般二维模糊控制器的通用规则，设计模糊控制器，充分利用模糊控制、内模控制、PID控制的优点。将所设计的系统应用于具有大时滞、大惯性特点的电厂主汽温控制系统检验其性能，仿真试验证明了这一方法具有很好的鲁棒性、控制精度和抗干扰能力。     

模糊自整定PID控制器的设计与仿真

常规PID控制器因结构简单、鲁棒性好、参数调整方便等,常被用于工业过程控制.但其参数整定是在获取被控对象数学模型的基础上根据一定的规则来确定的,难以适应复杂多变的控制系统.针对其参数整定效果不良、调试时间长、对被控对象适应性差等缺点,将模糊控制与PID控制相结合,设计了模糊自整定PID控制器.在常规PID控制器基础上,根据相应的模糊规则进行模糊推理,实现PID参数的在线自整定.仿真结果表明,模糊自整定PID控制器,不仅具有模糊控制快速、适应性强等优点,又有PID控制精确度高的特点,使系统有较好的控制作用,因此具有较好的工业应用前景.     

Fuzzy-PID控制起动机性能测试系统的研究

针对起动机性能测试系统,设计由标准ＰＩＤ控制器和模糊自整定机构组成的模糊自整定ＰＩＤ控制器和其模糊自整定机构通过调整参数ａ来在线整定ＰＩＤ参数以求控制的快速必和鲁棒性,实际运行结果表明起动机性能测试系统检测精度高,快速性好,可靠同,已稳定运行于复杂环境的电机生产线上。     

基于模糊自适应整定PID 的活套高度控制系统

针对板带热连轧机传统活套高度控制策略存在的问题，提出用模糊自适应整定PID的控制策略．控制器输入取活套量的偏差e和偏差变化率ec，输出取PID控制器3个参数的修正量，从而实现了PID参数的在线自整定．通过MATLAB语言，进行了传统PID控制与模糊自适应整定PID控制动态性能的仿真比较，结果表明采用模糊自适应整定PID控制可明显提高活套高度控制系统的动态性能．     

Developments of fuzzy PID controllers

Abstract: This paper describes the development and tuning methods for a novel self-organizing fuzzy proportional integral derivative (PID) controller. Before applying fuzzy logic, the PID gains are tuned using a conventional tuning method. At supervisory level, fuzzy logic readjusts the PID gains online. In the first tuning method, fuzzy logic at the supervisory level readjusts the three PID gains during the system operation. In the second tuning method, fuzzy logic only readjusts the proportional PID gain, and the corresponding integral and derivative gains are readjusted using the Ziegler–Nichols tuning method while the system is in operation. For the compositional rule of inferences in the fuzzy PID and the self-organizing fuzzy PID schemes two new approaches are introduced: the min implication function with the mean of maxima defuzzification method, and the max-product implication function with the centre of gravity defuzzification method. The fuzzy PID controller, the self-organizing fuzzy PID controller and the PID controller are all applied to a non-linear revolute-joint robot arm for step input and path tracking experiments using computer simulation. For the step input and path tracking experiments, the novel self-organizing fuzzy PID controller produces a better output response than the fuzzy PID controller; and in turn both controllers exhibit better process output than the PID controller.     

The SOF-PID controller for the control of a MIMO robot arm

The application of a self-organizing fuzzy proportional-integral-derivative (SOF-PID) controller to a multiple-input-multiple-output (MIMO) nonlinear revolute-joint robot arm is studied in this paper. The SOF controller is a learning supervisory controller, making small changes to the values of the PID gains while the system is in operation. In effect, the SOF controller replaces an experienced human operator, which otherwise would have readjusted the PID gains during the system operation. The three PID gains are tuned using classical tuning techniques prior to the application of the SOF controller at the supervisory level. Two trajectories of step input and path tracking were applied to the SOF-PID controller at the setpoint. For comparison purposes, the same experiments were repeated by using the self-organizing fuzzy controller (SOFC) and the PID controller subject to the same information supplied at the setpoint. For the step input, the SOF-PID controller produced a aster rise time, a smaller steady state error, and an insignificant overshoot than the SOFC and the PID controller. For the path tracking experiments, better results were obtained.     

Analysis of direct action fuzzy PID controller structures

The majority of the research work on fuzzy PID controllers focuses on the conventional two-input PI or PD type controller proposed by Mamdani (1974). However, fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. This paper investigates different fuzzy PID controller structures, including the Mamdani-type controller. By expressing the fuzzy rules in different forms, each PLD structure is distinctly identified. For purpose of analysis, a linear-like fuzzy controller is defined. A simple analytical procedure is developed to deduce the closed form solution for a three-input fuzzy inference. This solution is used to identify the fuzzy PID action of each structure type in the dissociated form. The solution for single-input-single-output nonlinear fuzzy inferences illustrates the effect of nonlinearity tuning. The design of a fuzzy PID controller is then treated as a two-level tuning problem. The first level tunes the nonlinear PID gains and the second level tunes the linear gains, including scale factors of fuzzy variables. By assigning a minimum number of rules to each type, the linear and nonlinear gains are deduced and explicitly presented. The tuning characteristics of different fuzzy PID structures are evaluated with respect to their functional behaviors. The rule decoupled and one-input rule structures proposed in this paper provide greater flexibility and better functional properties than the conventional fuzzy PHD structures.     

Quantitative design and analysis of fuzzy proportional-integralderivative control a step towards autotuning

In this paper, a thorough mathematical analysis is proposed for designing and tuning fuzzy proportional-integral-derivative (FZ-PID) control in order to achieve a better performance and simpler design. The quantitative model of FZ-PID, derived for the mathematical analysis and gain design, consists of a nonlinear relay and a nonlinear proportional-integral-derivative (PID) controller. This nonlinear model can be treated as of a PID nature around the equilibrium state under certain approximations. Through direct comparison with the conventional PID control, the connection between the scaling gains and the control actions is expressed in an explicit mathematical form. This theoretical analysis reveals that FZ-PID leads to more damping and hence less oscillation than do its conventional counterparts. This could be one of the reasons why fuzzy logic control can achieve a robust performance. A less coupled gain structure is further proposed to decouple the influence of the scaling gains and to disclose the major contribution of each gain to the different aspects of the control performance. Consequently, the systematic design and tuning method of the conventional PID control can be applied to the initial gain design and the fine tuning of the FZ-PID control. The simulation results confirm the effectiveness of the method proposed. This research is actually an important step towards the possible autotuning of the fuzzy controller.     

基于FPAA的模糊自整定PID控制器设计

为提高过程控制的响应速度,提出了一种基于现场可编程模拟阵列(FPAA)模糊自整定PID控制器的硬件实现方法。在8块AN221E04芯片中实现模拟乘法器、求小求和以及除法等单元电路,由各单元电路组合成完整的控制器。作为硬件电路,该控制器与软件编程实现的模糊PID控制器相比具有很强的实时性;作为纯模拟电路,该控制器内部传输信号均为连续值的模拟量,不需要A/D、D/A转换电路,与采用数字电路实现的控制器相比具有电路简单、运算速度快的特点。仿真实验结果表明：基于FPAA的模糊自整定PID控制器超调量小、稳态误差小,控制器响应时间降到了微秒级。     

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。     

Nonlinear CSTR control system design using an artificial bee colony algorithm

This paper proposes a novel controller design method based on using artificial bee colony (ABC) algorithms for an unstable nonlinear continuously stirred tank reactor (CSTR) chemical system. Such CSTR process is highly nonlinear and its dynamic is significantly dominated by system parameters. It is a good challenge to access the controller design performance when the controller is applied in the CSTR control system. The commonly used proportional–integral-derivative (PID) controller is taken into account in this study, and tuning three PID control gains is carried out by the artificial bee colony algorithm. With the use of the optimal ABC algorithm, PID controller gains can be derived suitably by means of minimizing the cost function given in advance. Finally, several control operations are provided to confirm the feasibility and effectiveness of the proposed method. We also discuss the influence of algorithm initial conditions on the control performance with many different tests.     

New methodology for analytical and optimal design of fuzzy PIDcontrollers

Describes a methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and, genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonlinear tuning parameters. The nonlinear proportional gain is explicitly derived in the error domain. A conservative design strategy is proposed for realizing a guaranteed-PID-performance (GPP) fuzzy controller. This strategy suggests that a fuzzy PID controller should be able to produce a linear function from its nonlinearity tuning of the system. The proposed PID system is able to produce a close approximation of a linear function for approximating the GPP system. This GPP system, incorporated with a genetic solver for the optimization, will provide the performance no worse than the corresponding linear controller with respect to the specific performance criteria. Two indexes, linearity approximation index (LAI) and nonlinearity variation index (NVI), are suggested for evaluating the nonlinear design of fuzzy controllers. The proposed control system has been applied to several first-order, second-order, and fifth-order processes. Simulation results show that the proposed fuzzy PID controller produces superior control performance to the conventional PID controllers, particularly in handling nonlinearities due to time delay and saturation     

基于模糊PID复合控制的异步电动机软起动器的设计

针对异步电动机直接起动电流较大的问题及传统比例-积分-微分( PID)控制和模糊控制在异步电动机软起动控制中的比较,提出了1种基于模糊PID复合控制的异步电动机软起动器的设计方法.根据对电动机起动特性的分析,在异步电动机起动的不同阶段分别采用模糊控制和PID控制,以达到最佳的起动效果.仿真结果表明,这种复合控制方法解决...     

模糊自适应PID控制器参数整定的研究

主要研究了模糊自适应PID控制器参数整定方法,给出了预估计PID参数值的经验公式和方法。用MATLAB软件对PID控制、模糊自适应PID控制的控制性能分别进行了仿真研究,结果表明参数模糊自整定PID控制具有良好的稳态精度和自适应能力。