干涉式闭环光纤陀螺仪的PSO-PID控制优化方法

控制系统的设计会对响应速度快且应用范围较广的数字干涉式闭环光纤陀螺(ICFOG)动态性能产生影响。通过分析ICFOG的工作原理,推导出闭环离散控制系统,并利用粒子群优化算法(Particle Swarm Optimization,PSO)对传统的PID控制器参数进行优化。基于这个优化过程,设计一种新型的PSO-PID复合控制器,以取代传统的PID控制器。通过与其他BP神经网络、模糊控制等方法进行对比凸显该控制方法的优越。通过数字仿真分析显示,跟踪速度相较于BP-PID控制方法提高了1.91倍,相对于PID控制方法提高了3.5倍,相对于F-PID控制方法提高了1.75倍。同时,控制精度相对于BP-PID控制方法提高了46.03%,相对于PID控制方法提高了66.30%,相对于F-PID控制方法提高了45.27%。结果显示,采用PSO-PID控制器能够快速达到控制目标且具有较小的超调量。

基于STM32的密炼机自整定PID温控系统设计

针对密炼机温度控制系统中人工整定PID带来的系统响应不及时、误差大等问题,该文设计了一种基于STM32的自整定PID温度控制系统。对于电动阀只能单极性调节问题,通过设置适当的工艺点来控制继电输出。为提高震荡曲线的辨识,采用参数归一化方法计算震荡曲线的临界增益。考虑密炼机的工作环境和系统响应曲线的频率特性,加入带有临界滞环控制的继电控制方法,提高了特征参数的精确性,更好地整定了PID参数。应用结果表明,基于STM32的PID整定温度控制系统能够将温度误差控制在1℃左右,且控制时间相比于人工PID控制系统提高了30%,极大地满足了密炼机的温度控制要求,具有良好的实用价值。

DCS中串级PID调节器的用户功能块设计及应用

为了研究串级PID调节器在DCS中的应用,选用一种基于ABB-800F软件自定义的用户功能块作为研究对象,对该软件自带PID通用连续调节控制块(C_CU)展开PID调节器面板及程序设计,增强其功能,通过密码解锁,实现一种能够直观进行图形化界面参数整定及调试的通用PID软调节器,既可以单回路PID控制,又可以串级PID控制,且能在编程组态中像功能块FBD指令一样使用。该用户功能块串级PID软调节器在某化工甲醛生产中应用,已经取得良好的效果。

基于BAS的模糊PID解耦算法在船舶动力定位中的应用

模糊PID应用于船舶动力定位控制时,因无法保证量化比例因子选取到最优值可能限制控制性能。基于某动力定位船舶的三自由度运动模型,利用串联补偿解耦算法消除船舶横荡与首摇控制量的相互影响,选取纵荡与横荡的时间乘绝对误差积分(Integrals of Time-weighted Absolute Error,ITAE)之和为目标函数,尝试利用天牛须搜索算法(Beetle Antennae Search algorithm,BAS)对模糊PID中的量化比例因子进行优化。利用Matlab/Simulink,采用PID、模糊PID、基于BAS的模糊PID等3种控制策略,对定点定位工况下动力定位船舶在无干扰和瞬时干扰条件运动响应进行仿真。研究发现,相比于PID和模糊PID,基于BAS的模糊PID在纵荡和横荡运动控制上可显著提高控制精度并减少超调量,进而可改善动力定位系统性能。

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology,a networked multi-agent control system is a key direction of modern industrial control systems,such as industrial Internet systems.This paper studies the tracking control problem of networked multi-agent systems with communication constraints,where each agent has no information on the dynamics of other agents except their outputs.A networked predictive proportional integral derivative(PPID)tracking scheme is proposed to achieve the desired tracking performance,compensate actively for communication delays,and simplify implementation in a distributed manner.This scheme combines the past,present and predictive information of neighbour agents to form a tracking error signal for each agent,and applies the proportional,integral,and derivative of the agent tracking error signal to control each individual agent.The criteria of the stability and output tracking consensus of multi-agent systems with the networked PPID tracking scheme are derived through detailed analysis on the closed-loop systems.The effectiveness of the networked PPID tracking scheme is illustrated via an example.

基于PSO改进BP算法的直流电子负载PID控制仿真

针对电子负载控制灵敏度低、稳定性差等问题,提出基于PSO-BP-PID的直流电子负载控制方法。分析电子负载基本结构,构建数学模型,分析电子负载在不同工作模式下的电流变化规律;建立三层BP网络模型,分别描述每层结构的输入与输出内容;为提高BP网络的学习能力,减少控制误差,将PSO算法作为学习算法,确定粒子群规模、惯性权重等重要参数,获得所有粒子适应度值,不断更新个体的位置与速度,当满足收敛条件时,输出最优解,实现控制参数的自适应调整;根据算法特征,设计控制器整体结构,利用该控制器即可实现直流电子负载控制。仿真结果表明,所提方法的控制误差小,响应速度快,且控制过程中能够有效抑制谐波。

Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

An intelligent control method based on artificial neural network for numerical flight simulation of the basic finner projectile with pitching maneuver

In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.

A PID Tuning Approach for Inertial Systems Performance Optimization

In the practice of control the industrial processes, proportional-integral-derivative controller remains pivotal due to its simple structure and system performance-oriented tuning process. In this paper are presented two approaches for synthesis the proportional-integral-derivative controller to the models of objects with inertia, that offer the procedure of system performance optimization based on maximum stability degree criterion. The proposed algorithms of system performance optimization were elaborated for model of objects with inertia second and third order and offer simple analytical expressions for tuning the PID controller. Validation and verification are conducted through computer simulations using MATLAB, demonstrating successful performance optimization and showcasing the effectiveness PID controllers’ tuning. The proposed approaches contribute insights to the field of control, offering a pathway for optimizing the performance of second and third-order inertial systems through robust controller synthesis.

基于MATLAB/Simulink工业机器人模糊PID阻抗控制仿真研究

针对工业机器人的控制精度与响应速度问题,提出一种基于位置的模糊PID阻抗控制算法,对机器人进行力控仿真研究,根据拉格朗日方程和Simulink仿真平台搭建六自由度工业机械臂控制仿真,对其进行正逆运动学及动力学分析,验证所提算法的有效性和适用性,结果表明该算法具有良好的控制效果,进一步降低控制过程的接触力与位置误差,提高机器人控制精度。

基于改进SSA优化PID的下肢康复机器人控制

针对下肢康复机器人训练过程中步态跟踪误差大的问题,提出一种改进麻雀搜索算法(ISSA)优化PID的控制策略。首先,利用拉格朗日方程对下肢机器人进行动力学分析,得到动力学模型;然后,通过引入Kent映射混沌初始化种群、Tent混沌扰动和柯西变异扰动,以及改变探索者-跟随者比例系数和探索者位置更新公式等方面对麻雀搜索算法进行改进,通过8种测试函数证实了算法改进的有效性;最后,在Matlab/Simulink中建立下肢机器人PID控制器和ISSA-PID控制器系统的仿真模型,以正常人体步态数据进行拟合得到的函数曲线作为系统实际输入进行跟踪实验。结果表明:相比于传统PID控制,ISSA-PID控制髋关节和膝关节的误差分别降低了63.3%和72.5%,实现了精准的步态跟踪,验证了该控制策略的有效性。

基于PSO算法优化模糊PID控制器的灵巧手抓取控制研究

随着仿生学的进展,机器人领域中五指灵巧手作为主要执行机构的重要性不断增强。然而,在抓取过程中,五指灵巧手常常面临内部作用复杂、速度缓慢和效率低等问题。为了应对这些挑战,该文提出了一种基于角度闭环模糊自适应控制算法。该算法采用模糊策略来推断灵巧手关节角度偏差与控制器参数之间的关系,并制定相应的模糊规则。通过实时调整控制器参数,该算法能够提高系统的稳定性和抓取效率。此外,通过建立ADAMS模型和相应的闭环控制系统,以提高实验过程的可视化程度。实验结果表明,通过采用粒子群算法(Particle Swarm Optimization Algorithm)优化模糊自适应PID算法并改进系统参数,相较于传统的PID算法,可以显著减少灵巧手在抓取过程中的关节抖动,并展现出更好的手指指尖接触力控制性能。

Exploring Variability in Sea Level at a Tide Gauge Station through Control Charts

Monitoring temporal changes in sea level is important in assessing coastal risk.Sea level anomalies at a tide gauge station,if kinematically conceived,include systematic variations such as trend,acceleration,periodic oscillations,and random disturbances.Among them,the non-stationary nature of the random sea level variations of known or unknown origin at coastal regions has been long recognized by the sea level community.This study proposes the analyses of subgroups of random residual statistics of a rigorously formulated kinematic model solution of tide gauge variations using X-bar and S control charts.The approach is demonstrated using Key West,Florida tide gauge records.The mean and standard errors of 5-year-long subgroups of the residuals revealed that sea level changes at this location have been progressively intensifying from 1913 to the present.Increasing oscillations in sea level at this locality may be attributed partly to the thermal expansion of seawater with increasing temperatures causing larger buoyancy-related sea level fluctuations as well as the intensification of atmospheric events including wind patterns and the impact of changes in inverted barometer effects that will alter coastal risk assessments for the future.

Vision Navigation Based PID Control for Line Tracking Robot

In a controlled indoor environment,line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots.A line tracking robot is a self-mobile machine that can recognize and track a painted line on thefloor.In general,the path is set and can be visible,such as a black line on a white surface with high contrasting colors.The robot’s path is marked by a distinct line or track,which the robot follows to move.Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation.Localization,automated map generation,autonomous navigation and path tracking is all becoming more frequent in vision applications.A visual navigation line tracking robot should detect the line with a camera using an image processing technique.The paper focuses on combining computer vision techniques with a proportional-integral-derivative(PID)control-ler for automatic steering and speed control.A prototype line tracking robot is used to evaluate the proposed control strategy.

Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

基于Smith预估模糊PID的浮选液位控制系统设计

浮选机内液位高低影响着浮选效果和生产稳定性,针对煤泥浮选中浮选机液位对浮选结果产生的影响,结合浮选液位控制系统的特点及其性能要求,采用了一种将Smith预估控制、模糊控制、PID控制结合的液位控制系统,并利用MATLAB中Simulink模块设计浮选液位仿真模型,进行仿真分析,同时改变液位以测试系统的稳定性。通过对传统PID、模糊PID及Smith预估模糊PID控制算法进行比较可知,液位控制系统采用Smith预估模糊PID算法,其控制效果由于传统PID和模糊PID控制,调节时间更短,稳定性更强,提高了浮选机液位的稳定性,能更好地满足浮选过程对液位的要求。

Smith预估模糊PID控制算法及其在粉末定量称重中的应用

针对上海科源电子科技有限公司研发的定量称重系统(由高精度抖粉装置与万分之一天平组成),在工作中因粉末密度、粉末流动性、颗粒大小、湿度、天平延时等因素造成的非线性和滞后等问题,采用Smith预估模糊PID控制器优化控制方法。首先通过理论分析,得出系统的传递函数,再构建Smith预估的模糊PID控制器,以适应系统的非线性、滞后等特性,最后将此算法代入MATLAB进行仿真并于实际系统中进行1 g定量抖粉实验。Smith预估模糊PID控制算法和传统PID算法的标准差分别为0.0020和0.0042,表明Smith预估模糊PID控制算法在实际环境中稳定性更好,能有效减小系统的称重误差。

基于Smith预估器的模糊PID调车自动驾驶系统速度控制研究

针对铁路站场调车作业的复杂性,研发基于调车的自动驾驶系统可降低劳动强度并提高车站作业效率,而速度控制策略是系统的重点和难点。根据调车牵引控制系统和制动控制系统特性,建立传递函数模型,并对模型参数的不稳定因素进行分析;利用Smith预估方法处理时滞系统的优势,结合模糊PID算法,设计基于Smith预估器的模糊PID控制器(简称新型控制器);通过模拟模型参数不稳定,分别使用阶跃响应曲线和司机实操速度曲线进行仿真,对比传统的PID控制器、模糊PID控制器与新型控制器的控制效果。结果表明:新型控制器适应能力更强,速度跟踪效果和停车精度都更高。

基于SSA-模糊PID的AUV姿态控制研究

针对AUV高精度、高稳定性姿态控制的提升需求,提出一种结合麻雀算法(SSA)和模糊PID控制的姿态控制器;采用麻雀算法对模糊PID控制器参数进行优化,并将寻优后模型用于算法的反馈补偿,有效解决了模糊PID控制过度依赖经验,难以应对水下复杂工况的问题;仿真结果表明,SSA-模糊PID控制器在AUV姿态调节中表现出较传统模糊PID控制器更好的响应速度和抗干扰能力,有效改善了AUV姿态控制性能;经实际应用验证,控制器在复杂工况下可快速收敛至期望姿态并维持稳定。

基于S7-1500 PLC的步进电机PID控制

通过对PLC的软件编程,实现了S7-1500 PLC对步进电机的PID控制。首先明确了PLC、步进电机和步进电机驱动器之间的电气连接关系;然后利用S7-1500 PLC配套的博途软件进行了PTO组态和轴工艺组态,基于HMI设计了人机交互界面,设计了PID控制器;最后搭建了实验系统,利用临界比例度法整定了PID参数。实验验证了步进电机PID控制的调整时间小于1min,位置精度小于0.02°。