基于Fuzzy-PID的棉花打顶升降装置设计与试验

为解决棉花打顶机作业过程中由于仿形时与刀盘移动滞后、定位精准度低,导致的棉花漏打、过打及伤苗的问题,基于模糊控制技术对棉花打顶装置高度控制系统进行研究。以3MDZF-6棉花打顶机升降系统为分析对象,确定了刀盘在升降过程中的定位精度要求。以液压阀-液压缸为对象,在AMESim中建立打顶升降装置的控制模型,并将其导入到MatLab中,设计相应的模糊规则和模糊控制器,对其进行仿真分析,从超调量和响应时间两方面验证了PID和模糊PID控制方法的可行性。仿真结果表明:无外界干扰的情况下,PID参数分别为100800、500、30时,输入信号达到稳态的响应时间为0.55s;模糊PID控制下输入信号达到稳态的响应时间为0.31s。经过对比分析固定参数PID控制和模糊PID控制在不同扰动下的控制效果,发现模糊PID控制系统的超调量为0.84%,输入信号达到稳态所需的时间为0.39s,小于固定参数PID的0.64s。该方法实现了打顶升降装置的位移控制,提高了刀盘的定位精度及控制系统的抗干扰性和鲁棒性,可为棉田环境下的棉花打顶升降装置的精确控制问题提供借鉴。

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

矿井带式输送机液压拉紧Fuzzy-PID控制技术研究

针对矿井传统带式输送机拉紧系统响应速度慢、调节能力差、拉紧控制时变性和非线性等问题,提出了一种矿井带式输送机液压拉紧系统Fuzzy-PID控制(基于模糊算法的PID控制)方法。首先,根据液压拉紧装置建立数学模型,其次通过Matlab内置的Simulink仿真库分别对Fuzzy-PID控制器和PID控制器的液压拉紧系统进行仿真,得出输送带拉紧张力启动响应阶段和张力突变的调节响应图,并做出对比分析。最后,通过试验测试来验证算法模型的有效性。仿真结果表明:矿井带式输送机液压拉紧Fuzzy-PID控制系统不仅在启动阶段还有张力突变过程中都具有更好的稳态性能、更快的响应速度。在拉紧装置启动响应阶段的张力超调量降低了13.5%、到达期望值的时间缩短了0.5 s。在拉紧装置张力突变即模拟拉紧和松带阶段,当张力增加时,Fuzzy-PID控制器的调节速度缩短了0.4 s,超调量下降了4%。当张力减少时,Fuzzy-PID控制器的调节速度缩短了0.3 s,超调量降低了2%。试验结果表明:采用Fuzzy-PID控制的效果更佳优异稳定,且损耗更小。对比于PID控制,Fuzzy-PID控制效果更为良好,平均时间缩短31%且总体趋于稳定。对于矿井带式输送机这种连续运输作业的设备,Fuzzy-PID控制技术为矿井带式输送带平稳运行提供了一定保障,不仅减少了电能浪费,也降低了维护保养带式输送机的保养成本。

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

Determination of AVR System PID Controller Parameters Using Improved Variants of Reptile Search Algorithm and a Novel Objective Function

Two novel improved variants of reptile search algorithm(RSA),RSA with opposition-based learning(ORSA)and hybrid ORSA with pattern search(ORSAPS),are proposed to determine the proportional,integral,and derivative(PID)controller parameters of an automatic voltage regulator(AVR)system using a novel objective function with augmented flexibility.In the proposed algorithms,the opposition-based learning technique improves the global search abilities of the original RSA algorithm,while the hybridization with the pattern search(PS)algorithm improves the local search abilities.Both algorithms are compared with the original RSA algorithm and have shown to be highly effective algorithms for tuning the PID controller parameters of an AVR system by getting superior results.Several analyses such as transient,stability,robustness,disturbance rejection,and trajectory tracking are conducted to test the performance of the proposed algorithms,which have validated the good promise of the proposed methods for controller designs.The performances of the proposed design approaches are also compared with the previously reported PID controller parameter tuning approaches to assess their success.It is shown that both proposed approaches obtain excellent and robust results among all compared ones.That is,with the adjustment of the weight factorα,which is introduced by the proposed objective function,for a system with high bandwitdh(α=1),the proposed ORSAPS-PID system has 2.08%more bandwidth than the proposed ORSA-PID system and 5.1%faster than the fastest algorithm from the literature.On the other hand,for a system where high phase and gain margins are desired(α=10),the proposed ORSA-PID system has 0.53%more phase margin and 2.18%more gain margin than the proposed ORSAPS-PID system and has 0.71%more phase margin and 2.25%more gain margin than the best performing algorithm from the literature.

Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

Optimal fuzzy PID controller with adjustable factors based on flexible polyhedron search algorithm

A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.

ACS algorithm-based adaptive fuzzy PID controller and its application to CIP-I intelligent leg

Based on the ant colony system(ACS)algorithm and fuzzy logic control,a new design method for optimal fuzzy PID controller was proposed.In this method,the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object.The designed controller,called the Fuzzy-ACS PID controller,was used to control the CIP-I intelligent leg.The simulation experiments demonstrate that this controller has good control performance.Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm,the real-coded genetic algorithm,and the simulated annealing,it was verified that the Fuzzy-ACS PID controller has better control performance.Furthermore,the simulation results also verify that the proposed ACS algorithm has quick convergence speed,small solution variation,good dynamic convergence behavior,and high computation efficiency in searching for the optimal input/output scaling factors.

采摘机器人机械手避障方法研究——基于遗传优化和模糊PID控制器

为了提高采摘机器人机械手移动的自动化程度,使其在移动过程中有效避开障碍物,将基于PID控制器的避障系统引入到了机械手的设计上,并采用遗传算法和模糊算法对控制器进行了优化,提高了机械手移动的准确性和平稳性。模拟采摘机器人机械手的作业环境,对机械手的避障功能进行了测试,结果表明:机械手可以成功躲避障碍物,且采用遗传和模糊算法优化的机械手具有更高的移动平稳性,对于提高果实采摘效率和质量具有重要的作用。

基于遗传算法的汽车主动悬架变论域模糊PID控制

针对1/4车主动悬架系统,提出一种基于遗传算法(genetic algorithm,GA)的变论域模糊比例-积分-微分(proportional-integral-differential,PID)控制方法.在建立主动悬架系统模型的基础上,引入变论域思想设计模糊PID控制器.为进一步改善控制器减振效果,采用GA来优化变论域中伸缩因子描述函数的参数.结果表明:相比PID、模糊PID与未优化的变论域模糊PID等控制方法,基于GA的变论域模糊PID控制方法在降低车身垂向加速度、改善乘坐舒适性方面具有优越性;所提控制方法对簧载质量和车辆行驶速度不确定性具备较强的鲁棒性.

基于PID的ROV运动控制仿真

针对观察型水下机器人在水下运动时易受暗流、波浪影响,造成操控困难、系统稳定性差等问题,建立遥控水下机器人(Remotely Operated Vehicle,ROV)不同运动的控制模型,考虑电机和导管螺旋桨推进器的传递函数对ROV控制系统的影响,确定定艏向和定深控制系统的闭环传递函数,结合模糊控制和比例积分微分(Proportional Integral Differential,PID)控制法,得到模糊PID控制器,基于MATLAB/Simulink环境进行ROV定深度运动仿真和ROV水平面艏向定偏角运动仿真。结果表明,与传统PID控制相比,模糊PID控制具有更优的ROV定艏向和定深度控制效果,不会发生超调现象,在抗干扰能力和响应速度方面具有明显的优势,可有效地实现ROV定艏向和定深度运动控制。

基于粒子群优化模糊PID控制的水厂加氯系统

水厂加氯过程具有非线性、大时滞等特点,采用传统的PID控制方式难以实现消毒剂精准投加。因此,以某采用次氯酸钠消毒系统的水厂为例,首先通过分析该水厂加氯系统工作原理,结合工程经验和运行数据确定了加氯过程的近似数学模型。然后综合使用粒子群优化算法、模糊控制算法和PID控制算法,设计了一种粒子群优化模糊PID控制器,并利用MATLAB软件搭建了粒子群优化模糊PID控制系统和传统PID控制系统的模型进行仿真验证,结果表明:相较于传统PID控制系统,粒子群优化模糊PID控制系统的超调量减少了89.36%,调节时间减少了46.63%,其抗干扰能力也更强,系统整体控制效果有了较大提升。最后使用基于粒子群优化的模糊PID控制法对水厂加氯控制系统进行改造,试运行后发现,新系统控制效果良好,出厂水游离氯值能够稳定在设定值附近。

基于单片机和PID算法的温度智能控制系统设计

为提高温度控制的智能化水平,设计一种智能温度控制系统。该系统以STC89C52单片机为控制器,采用PID算法控制温度,具有语音播报和手机远程控制等功能。采用DS18B20温度传感器采集环境温度;设计LCD12864显示电路实时显示当前温度、温度上下限以及温度状态;设计WT588D语音提醒电路,当测量温度小于下限或大于上限时发出语音提醒;设计按键电路实现温度上下限值的设定;设计蓝牙通信电路,与手机APP通信,实现远程控制;采用PID算法输出控制量,控制固态继电器驱动加热或降温装置,实现温度控制。其次,对温度控制系统的硬件和软件进行设计,并制作实物进行运行测试。实验结果表明,所设计的温度控制系统能够很好地实现温度控制,从而达到预期效果,且操作方便、成本低,具有较强的应用价值。

基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法

目前常规的粗纱机出料传动系统PID参数优化方法主要通过结合被控对象的稳态增益情况构建出优化函数,实现PID参数优化整合,忽略了实际运行工况下的干扰成分,导致参数优化效果不佳。对此,提出基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法。首先结合PID的系统阶跃响应曲线,以被控量的偏差变化率作为主要参数选取性能指标;然后通过引入负荷扰动模块以及频率干扰模块,对PID调节模块进行建模分析;最后结合模糊-遗传算法对最优适应度值进行求解,从而实现PID参数的有效优化,并对提出的方法进行优化效果检验。最终测试结果表明,采用提出的方法对PID参数进行优化整合时,控制输出曲线与理论输出曲线的拟合程度更高,具备较为理想的优化效果。

基于ISSA-Fuzzy-PID算法的无刷直流电机调速控制系统

为了使无刷直流电机(BLDCM)从复杂多变的非线性关系中找出最佳PID参数,提出了一种基于改进麻雀算法(ISSA)优化模糊(fuzzy)控制的调速系统。根据BLDCM工作原理及控制方法在MATLAB平台上搭建仿真模型并加入反向学习策略初始化麻雀种群,形成非线性时变控制系统,并将该优化系统与传统PID以及模糊PID(fuzzy-PID)控制系统进行对比分析。仿真结果表明,基于ISSA-Fuzzy-PID的调速控制系统有较快的动态响应,有效增强了BLDCM转速控制的精度和鲁棒性。

基于变论域模糊PID的金属热处理过程温度控制方法

为高效且安全地提取金属合金内的可用材质并分析其性能,利用变论域模糊PID技术,实现对热处理过程的温度控制。设定在金属规则状态不变的情况下,论域会随着偏差的缩减出现伸缩,即需要增添新的规则。若偏差率能够支持模糊量化取整,控制器的伸缩因子可能会陷入无法取值的情况。此时,通过二元函数分片双一次插值法计算伸缩因子,在临近分档之间填充新规则,确保伸缩因子取值的连续性。然后,在模糊PID控制过程中加入变论域,依靠控制器实现对金属热处理过程温度的控制。根据实验验证情况可知:该方法有效提高了控制效果,在应用该方法后,缩短了温度控制时间,在100s内就可以是加热温度到达拟定值。

爆胎车辆动力学分析及模糊PID控制优化策略研究

车辆通过控制系统提高行驶的稳定性,但在爆胎时容易导致车辆行驶失去稳定性,从而造成车辆发生侧翻现象。为改善车辆动力学控制系统输出效果,建立了车辆轮胎动力学模型。引用模糊比例-积分-微分(PID)控制器,给出了模糊PID控制器输出参数与误差和误差变化率的关系图。提出人群搜索算法,利用人群搜索算法迭代搜索原理对模糊PID控制器参数进行寻优。以车辆2种行驶路况为例,利用Matlab软件对爆胎车辆的稳定性进行仿真,比较和分析爆胎车辆优化控制系统的输出效果。结果显示:采用模糊PID控制系统,爆胎车辆产生的偏航角、俯仰角加速度和侧倾角加速度较大。采用人群搜索算法优化模糊PID控制系统,爆胎车辆产生的偏航角、俯仰角加速度和侧倾角加速度较小。爆胎车辆采用人群搜索算法优化后的模糊PID控制器,不仅响应速度快,而且行驶的稳定性较好。

多策略改进粒子群优化AGV模糊PID控制

为解决AGV在复杂环境下控制精度低下、响应速度慢和鲁棒性差等问题,提出一种基于改进粒子群优化模糊PID控制方法。在粒子群算法(PSO)引入Logistic混沌映射对种群进行初始化,其次对惯性权重和学习因子进行非线性控制更新,提升种群寻优能力和避免陷入局部最优;选取9个测试函数验证改进PSO算法效果。仿真结果表明改进PSO在寻优精度和收敛速度都优于其他3种算法,而且不易陷入局部最优。最后对被控系统进行效果验证,结果表明改进PSO优化模糊PID控制器在常规和外部干扰两种环境下控制性能都优于传统PID和模糊PID,具有高可靠性、高控制精度,满足系统要求。

正压呼吸防护面罩中无刷电机的模糊PID控制

正压呼吸防护面罩是作为医护工作者抗击新型冠状病毒(SARS-CoV-2)所使用的个体防护装备。本文忽略呼吸扰动等因素对送风子系统所产生的干扰,以送风子系统中的无刷直流电机为研究对象,建立无刷直流电机的数学模型;在MATLAB/Simulink环境中建立无刷直流电机转速PID控制模型,但由于无刷直流电机存在非线性、时变性等特点,导致PID控制对送风子系统中无刷直流电机的控制效果并不理想。然而,由于模糊控制不需要被控对象的精确模型,所以可以使用模糊PID来完成对送风子系统中无刷直流电机的控制优化。通过仿真实验结果表明:使用模糊PID控制系统的稳定性优于PID控制系统,无刷直流电机控制性能得到提升。

应用模糊PID自修正的电镀槽液温度控制方法

电镀槽液温度自动控制过程属于典型的混沌过程,在温度采集的过程中存在明显的非线性波动。典型的比例-积分-微分(PID)控制算法在这种混沌特性与非线性特性干扰下,存在控制精度较低、稳定性和鲁棒性较差等问题。此外,为解决非线性问题,PID算法需要循环迭代计算,存在控制时滞问题。以模糊控制为基础,提出了基于模糊PID的电镀槽液温度自动控制方法。该方法先设计温度数据采集结构,并将移动平均滤波、温度修正算法引入到采用的数据采集结构中,完成电镀槽液的实时温度数据采集。然后将采集到的温度数据作为构建的模糊PID控制器的输入。利用模糊控制规则引入修正因子,实现电镀槽液温度的自动控制。考虑到电镀槽液的时滞特性,在控制器中加入粗糙预估参考模型,对该特性加以抑制,提升控制性能。最后应用实验证明了所提方法的先进性。实验结果表明:所提方法具有较高的控制精度和效率,能够有效降低超调量和波动,应用效果较好。