IMC based robust PID controller tuning for disturbance rejection

It is well-known that the IMC-PID controller tuning gives fast and improved set point response but slow disturbance rejection. A modification has been proposed in IMC-PID tuning rule for the improved disturbance rejection. For the modified IMC-PID tuning rule, a method has been developed to obtain the IMC-PID setting in closed-loop mode without acquiring detailed information of the process. The proposed method is based on the closed-loop step set point experiment using a proportional only controller with gain K_(c0). It is the direct approach to find the PID controller setting similar to classical Ziegler-Nichols closed-loop method. Based on simulations of a wide range of first-order with delay processes, a simple correlation has been derived to obtain the modified IMC-PID controller settings from closed-loop experiment. In this method, controller gain is a function of the overshoot obtained in the closed loop set point experiment. The integral and derivative time is mainly a function of the time to reach the first peak(overshoot). Simulation has been conducted for the broad class of processes and the controllers were tuned to have the same degree of robustness by measuring the maximum sensitivity, Ms, in order to obtain a reasonable comparison. The PID controller settings obtained in the proposed tuning method show better performance and robustness with other two-step tuning methods for the broad class of processes. It has also been applied to temperature control loop in distillation column model. The result has been compared to the open loop tuning method where it gives robust and fast response.

A closed-loop particle swarm optimizer for multivariable process controller design

Design of general multivariable process controllers is an attractive and practical alternative to optimizing design by evolutionary algorithms (EAs) since it can be formulated as an optimization problem. A closed-loop particle swarm optimization (CLPSO) algorithm is proposed by mapping PSO elements into the closed-loop system based on control theories. At each time step, a proportional integral (PI) controller is used to calculate an updated inertia weight for each particle in swarms from its last fitness. With this modification, limitations caused by a uniform inertia weight for the whole population are avoided, and the particles have enough diversity. After the effectiveness, efficiency and robustness are tested by benchmark functions, CLPSO is applied to design a multivariable proportional-integral-derivative (PID) controller for a solvent dehydration tower in a chemical plant and has improved its performances.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

PID Controller Stabilization for First-order Integral Processes with Time Delay

Due to the widespread application of the PID controller in industrial control systems, it is desirable to know the complete set of all the stabilizing PID controllers for a given plant before the controller design and tuning. In this paper, the stabilization problems of the classical proportionalintegral-derivative （PID） controller and the singleparameter PID controller （containing only one adjustable parameter） for integral processes with time delay are investigated, respectively. The complete set of stabilizing parameters of the classical PID controller is determined using a version of the Hermite-Biehler Theorem applicable to quasipolynomials. Since the stabilization problem of the singie-parameter PID controller cannot be treated by the Hermite-Biehler Theorem, a simple method called duallocus diagram is employed to derive the stabilizing range of the single-parameter PID controller. These results provide insight into the tuning of the PID controllers.

双缸液压驱动系统灰色预测模糊PID控制研究

为了提高双缸液压驱动系统非线性变化力的跟踪精度,使驱动力变化相对稳定,设计了灰色预测模糊比例积分微分(PID)控制器,并对驱动力跟踪效果进行仿真验证。为了对双缸液压驱动系统工作原理进行介绍,绘制了双缸液压驱动系统装置简图。针对传统PID控制器进行改进,结合模糊推理和灰色预测理论,设计出灰色模糊PID控制器,并且给出了双缸液压驱动系统控制过程。利用灰色补偿提高控制器的抗干扰能力,采用Matlab软件对双缸液压驱动系统非线性力的变化跟踪进行仿真,与改进前的控制效果进行对比。结果显示:在无干扰环境中,采用PID控制、模糊PID控制和灰色预测模糊PID控制方法,均能提高双缸液压驱动系统力的变化跟踪精度,这3种控制器控制效果相差不大。在有干扰环境中,灰色预测模糊PID控制方法明显优于PID控制和模糊PID控制方法。双缸液压驱动系统采用灰色预测模糊PID控制方法,能够抑制外界波形的干扰,从而提高控制系统的稳定性。

双闭环PID应用下投篮机器人路径跟踪控制研究

投篮机器人路径图像噪声会影响机器人路径跟踪控制效果,导致投篮机器人偏离正常轨迹,为此提出双闭环PID应用下投篮机器人路径跟踪控制方法。分析投篮机器人架构,利用OpenMv视觉识别方法采集投篮机器人路径图像,结合小波阈值算法对采集到的图像实施去噪处理,从而获取清晰的投篮机器人路径图像。根据图像去噪处理结果,将曲线拟合法与特征点检测法相结合,实现投篮机器人路径识别。根据投篮机器人路径识别结果确定路径实际偏移量,结合推动器实现位置、移动速度建立的双闭环PID控制器,从而实现投篮机器人路径跟踪控制。实验结果表明,该方法的投篮机器人路径图像去噪熊效果好、跟踪控制效果好,充分验证了该方法的有效性。

Digital pulsed MIG welding machine based on adaptive fuzzy controller

Digital pulsed metal inert gas welding machine with double closed-loop control mode is designed and implemented. It realizes precision control for real time energy and demonstrates the flexibility of digital control. Test results of design prototype show that the designed control strategy can effectively adapt to the change of arc length and achieve ideal droplet transfer via one drop per pulse mode. Thus the welding process is stable and the weld bead is good.

基于AWF-DPID控制的同步Buck变换器研究

针对当前各种电子设备不断发展对电源管理芯片的精度、速度等要求越来越高的趋势,提出一种基于模糊逻辑的反计算法抗饱和双环PID(AWF-DPID)控制策略,实现同步Buck变换器的恒压限流功能。在双环PID(DPID)的基础上,设计一个二维模糊控制器,实时调整电压环输出参数,在电压环输出设计一个反算法抗积分饱和模块,从而调节Buck变换器的脉冲宽度,更高效精准地实现控制。变换器在10 kHz的频率下工作,给出变换器参数通过软件对不同控制策略进行仿真。结果表明,在实现恒压限流的相同控制目标下,AWF-DPID控制较其他控制响应更迅速、超调量更小稳态误差更小并且纹波系数更小;变输出指令下电压跟随性最好,有良好的动态特性。

A Fuzzy Controller for Blood Glucose-Insulin System

Diabetes therapy is normally based on discrete insulin infusion that uses long-time interval measurements. Nevertheless, in this paper, a continuous drug infusion closed-loop control system was proposed to avoid the traditional discrete approaches by automating diabetes therapy. Based on a continuous insulin injection model, two controllers were designed to deal with this plant. The controllers designed in this paper are: proportional integral derivative (PID), and fuzzy logic controllers (FLC). Simulation results have illustrated that the fuzzy logic controller outperformed the PID controller. These results were based on serious disturbances to glucose, such as exercise, delay or noise in glucose sensor and nutrition mixed meal absorption at meal time.

基于模糊自整定PID的双容水箱串级液位控制系统研究

双容水箱串级液位控制具有抗干扰能力强、超调量小、过渡过程较短等特点。传统的PID算法和参数整定方法难以达到期望的控制效果。因此,针对双容水箱串级液位控制,利用模糊推理的方法实现在线自整定PID参数,设计相应的模糊PID控制器,基于Simulink仿真建模,对比传统的PID与模糊自整定PID输出响应曲线发现,该模糊自整定PID系统具有更好的鲁棒性,抑制系统超调以及对控制参数变化的自适应能力更强。

80 MN压剪试验机竖向加载模糊PID控制系统的设计

为了稳定、精确、可靠地实施超大力值竖向加载,以80 MN压剪试验机为对象,对其竖向加载装置的机械结构、液压系统以及控制系统进行总体设计;建立位置-压力双闭环PID控制算法的数学模型,并设计模糊PID控制器;最后,通过AMESim-Simulink对控制系统进行耦合仿真,获取位移与试验力的时域响应曲线,并在80 MN压剪试验机上进行竖向加载试验以验证控制系统的可靠性。结果表明:竖向加载模糊PID控制系统使竖向加载在220 s后达到稳态,位移误差与试验力误差均小于0.05%,此控制系统的稳定性、精确性和可靠性得到验证。

输灰系统杆驱机构双缸闭环同步模糊PID控制

为了提高输灰系统杆驱机构双缸同步控制精度,设计了一种推进过程模糊比例-积分-微分(PID)控制方案,采用闭环同步控制。构建了模糊PID控制器,并通过Simulink完成仿真测试,验证了推进过程的同步控制性能。研究结果表明:速度信号发生了先加速,之后进入稳定速度,最后再减速。低速下,以模糊PID控制的双缸最大同步误差为0.085 mm,在稳定状态下的误差为0.002 2 mm;高速下,以模糊PID控制的双缸最大同步误差降低至0.13 mm,在稳定状态下的误差减小为0.03 mm。无论是高速还是低速,模糊PID控制相对于传统PID控制方式表现出更低的双缸同步误差,可以获得更高的系统控制精度。

杆驱工业机械臂双缸RBF优化模糊PID同步控制研究

为了提高杆驱工业机械臂双液压缸同步控制精度,设计了一种RBF优化模糊PID控制方法,并在Simulink平台完成性能仿真。研究结果表明:速度信号发生了先加速,之后进入稳定速度,最后再减速。低速下,以RBF优化模糊PID控制的双液压缸最大同步误差约为0.08 mm,稳定状态下的误差约为0.01 mm;高速下,以RBF优化模糊PID控制的双液压缸最大同步误差降低至0.11 mm,在稳定状态下的误差减小为0.02 mm。该研究有助于提供工业机器人控制精度,提高双臂协作效率。

基于DMC算法的精馏塔精馏段温度预测-PID双层控制系统应用分析

以精馏塔精馏段温度控制为例,提出基于动态矩阵控制(DMC)算法的预测-PID双层控制方案,并通过MATLAB/Simulink联合仿真方法,对PID-PID、预测-PID两种双层控制系统进行仿真对比分析,得出预测-PID双层控制系统具有跟踪性能好、超调量小、调节时间短且抗干扰能力强的优点。

基于模糊T-S型内模PID控制算法的无刷直流电机仿真分析

针对无刷直流电机(BLDCM)双闭环控制调速系统的控制响应速度慢、转速波动较大等问题,提出一种模糊神经网络与内模控制相结合的驱动方式。该方式利用Matlab/Simulink来构建一种基于BLDCM和控制器的电梯一体式限速器仿真模型,得到BLDCM的速度、转矩响应曲线。仿真分析和实验结果均表明,模糊T-S型内模PID控制算法在响应速度、转速误差、抗干扰能力和控制精度等性能方面优于内模PID控制算法与常规双闭环PID控制系统。该研究可为模糊神经网络T-S型内模PID算法在电梯一体式限速器上的应用积累经验。

基于西门子PLC的双闭环PID控制在橡胶制品挤出上的应用

现有轮胎生产技术中,轮胎产品中的主要半制品橡胶部件需要采用挤出工艺进行生产,半制品挤出过程是生产汽车轮胎必不可少的工艺环节,挤出制品的质量与精度直接影响到轮胎产品的最终质量与精度,也影响到轮胎生产的成本。解决稳定性差,挤出精确性差问题迫在眉睫。本文论述的控制系统采用一种串联双闭环PID算法进行速度的闭环控制,能够较好的解决现有轮胎半制品挤出生产技术中稳定性差和挤出精确性差的问题。

用于无功静补系统的模糊-PID控制方法

简要分析了静止型无功补偿器(SVC)的补偿原理,针对SVC系统的非线性,提出了一种用于无功静补系统的模糊-PID控制方法。该模糊-PID控制结合了模糊和PID两种控制方式的优点,根据预先设定的偏差范围在两种控制方式下自动切换。在这种混合控制方法中,采用模糊控制实现动态过程的快速调节;采用PID控制实现稳态过程的精确调节。分别将该模糊-PID控制器与传统的PID控制器应用于实验样机,对不同的负载工况进行反复实验,结果表明该控制器具有更好的控制精度,更快的动态响应速度以及更强的鲁棒性。

双闭环Buck变换器系统模糊PID控制

针对传统线性PID控制对复杂控制对象难以建模及人工整定经验缺乏等问题,提出了一种双闭环Buck变换器系统的模糊PID控制策略。首先,设计了电压外环和电流内环结构以同时提高系统的抗扰性和跟随性;其次选择高斯函数和三角形函数相结合的隶属度函数以使控制器对小误差的灵敏度得以增强;接着,针对PID参数分别设计了3个子推理器并通过基于专家经验的规则库制定出Buck变换器的模糊规则,可以使控制器不依赖于Buck变换器系统精确的数学模型,从而克服传统PID控制导致的输出电压高超调、振荡等缺点;最后,设计了一套新型双闭环Buck变换器硬件系统,利用STM32单片机将模糊PID算法首次用于控制变化速度快、时滞小的被控量。实验结果表明:模糊PID控制策略不仅能够提高输出电压跟踪精度,还能有效抑制负载扰动及参数摄动,在阶跃启动下,系统输出电压超调量低于10%,调节时间低于3ms;与传统PID单环系统相比,其输出电压纹波、扰动下的最大动态压降和恢复时间均减小了一个数量级以上。

基于模糊PID的酶免分析仪加样臂运动控制

为了保证全自动酶免分析仪加样臂运动的低速稳定性和位置精度,建立了加样臂运动控制系统。根据系统结构模型分析低速运行时爬行现象产生的原因,使用位置环PID、速度环模糊自适应PID的双闭环控制算法,改善低速爬行现象。并基于大量工程实验整定,选取了合适的模糊集合、模糊规则和PID参数论域取值。实测运行结果表明,在0.05 m/s的速度运行,能够保证速度误差小于2%,位置精度为±0.1 mm。算法满足了加样臂运行精度和稳定性要求。

双纵模热稳频激光源的模糊PID控制研究

为了满足激光拍频干涉仪所需要的高的频率稳定性的激光光源,研究了双纵模热稳频的机理。以控制激光管放电电流为主要热控制方式及自创的对激光管进行感应加热作为微量控制的先进方法为控制手段,采用模糊控制理论与专家系统相结合的控制策略,建立模糊PID控制器,对双纵模激光源进行稳频。无须建立被控对象数学模型,对时滞、非线形和时变性具有一定的适应能力。实验结果显示,稳频精度无明显变化,但预热时间明显缩短,抗干扰性明显增强,强干扰后也能迅速稳频。