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.

Improved control of intelligent excavator using proportional-integral-plus gain scheduling

Consider the design and implementation of an electro-hydraulic control system for a robotic excavator, namely the Lancaster University computerized and intelligent excavator (LUCIE). The excavator was developed to autonomously dig trenches without human intervention. One stumbling block is the achievement of adequate, accurate, quick and smooth movement under automatic control, which is difficult for traditional control algorithm, e.g. PI/PID. A gain scheduling design, based on the true digital proportional-integral-plus (PIP) control methodology, was utilized to regulate the nonlinear joint dynamics. Simulation and initial field tests both demonstrated the feasibility and robustness of proposed technique to the uncertainties of parameters, time delay and load disturbances, with the excavator arm directed along specified trajectories in a smooth, fast and accurate manner. The tracking error magnitudes for oblique straight line and horizontal straight line are less than 20 mm and 50 mm, respectively, while the velocity reaches 9 m/min.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Fractional Order Proportional Integral Derivative Controller Design and Simulation for Bioengineering Systems

This paper deals with the study of fractional order system tuning method based on Factional Order Proportional Integral Derivative( FOPID) controller in allusion to the nonlinear characteristics and fractional order mathematical model of bioengineering systems. The main contents include the design of FOPID controller and the simulation for bioengineering systems. The simulation results show that the tuning method of fractional order system based on the FOPID controller outperforms the fractional order system based on Fractional Order Proportional Integral( FOPI) controller. As it can enhance control character and improve the robustness of the system.

Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.

Improvement of one-cycle controller by use of proportional integral differential controller

The main advantage of one-cycle control is its ability to reject input disturbance in one-cycle. Despite this great ability, it can not provide good responses in following commands and rejecting load disturbance. This study explores the way to overcome these problems by using another controller. Although the idea of using output feedback has been used in previous works, by considering a simple model for one-cycle controller, the design of the controller has become simpler in this work. In the proposed method, difficult mathematical modeling is avoided. Based on decupling of effects of feedback and input voltage disturbance, a simple model for one-cycle controller has been given. Therefore, by employing a conventional averaging method and the model of one-cycle controller, design of proportional integral differential controller has become straightforward.

Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

数控压机伺服控制系统复合控制器I-ABC与PID优化

为了提高数控压机伺服控制系统的控制精度,针对伺服控制系统运行控制过程构建数学模型,在人工蜂群算法基础上融入了云分析模型,之后采用改进人工蜂群算法(Improved Artificial Bee Colony,I-ABC)调节比例-积分-微分(Proportional Integral Differential,PID)参数,建立了一种复合控制方法。研究结果表明:以I-ABC进行PID控制时,可以使幅度差降低到0.4%,相位差基本在-0.54°之内,系统加载精度也获得了明显提升,表现出了更优的跟踪性能。以I-ABC进行PID控制时,能够对多余力起到明显抑制作用,响应速度也获得明显提升,可以有效满足系统的准确控制要求。在系统内加入干扰信号,引入I-ABC实施PID调节可以减小系统超调量,还可以获得更短调节时间,使系统获得更强抗干扰性能。

基于改进麻雀优化PID的波浪补偿控制方法

随着海上风电“十四五”规划的不断推动,在深远海域对兆瓦级大功率海上风机的需求量随之增加,其规模也在不断扩大。但是,在吊运、安装等海上工作过程中,复杂海浪对船舶产生的持续影响导致风机安装的精度和效率大幅下降,甚至会对人员安全以及财产造成重大损失。在深远海域复杂海况下对工程船舶进行有效的波浪补偿,可提供稳定的作业环境以保证精准高效地完成各项工作,因此,本文提出了一种基于改进麻雀优化PID的波浪补偿控制方法并将其应用于Stewart补偿平台。首先,建立波浪补偿平台动力学以及运动学反解模型,并设计正解模型迭代求解算法。随后,使用PID进行波浪补偿控制,并通过麻雀搜索算法优化参数。接着,采用Circle混沌映射对其进行初始化分布,以解决初始化不均匀的问题;并采用动态自适应加权、柯西突变以及反向学习以提升算法全局寻优能力。最后,生成4~6级海况下的某工程船运动数据作为系统输入,利用MATLAB和Simulink软件平台搭建模型进行补偿控制验证,并在Stewart硬件平台上做补偿试验。结果表明,改进麻雀搜索算法具有较快的收敛速度、较高的精度和更好的寻优能力,优化后的PID控制方法更适合用于复杂海况下波浪补偿平台的控制优化,可为大功率海上风机安装的补偿平台控制系统设计提供参考。

有源电力滤波器补偿的PI解耦控制技术研究

电网中电压和电流波形的失真会产生谐波,导致电网功率因数降低,并影响电力系统的稳定性和可靠性。为了确保电力系统的正常工作,研究了基于有源电力滤波器补偿的比例积分(PI)解耦控制技术。设计了基于二极管钳位式的有源电力滤波器模型。结合基尔霍博电压法,降低控制谐波和解除部分变量耦合。针对设备非线性产生的谐波,分析有源电力滤波器的可逆性,获得输入雅可比矩阵,以实现滤波器旋转坐标的线性化。利用变换矩阵转换转动角速向量,输入谐波的幅度,输出电流取样延迟,完成无差PI解耦控制。试验结果表明,所提技术能够有效解耦滤波器的谐波电流成分,从而补偿电网中的失真电流。该技术可以减少谐波对电力系统的整体影响,保证设备的正常运行。

基于神经网络PI的电静液作动器温度补偿控制方法研究

电静液作动器(Electro-hydrostatic Actuator,EHA)作为一种高性能集成化的动力执行器,广泛应用于航天航空、工业生产和军事领域。在不同油液温度下,液压油的体积弹性模量、黏度等性质会发生变化,从而对EHA的控制精度产生影响。针对此问题,首先建立了EHA数学模型;其次,设计了反向传播(BP)神经网络对比例积分控制器(PI)控制参数进行在线调节,补偿温度变化对跟踪精度的影响;最后,通过实验验证了传统PI控制的EHA跟踪精度与温度变化有着密切关系,并将BPPI控制器与PI控制器进行实验对比。实验结果表明,所设计的BPPI控制器在不同油液温度下平均跟踪误差之间的差值较PI控制器降低80%以上;且在相同温度下,平均跟踪误差较PI控制器降低60%以上。

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

基于PI控制的内燃动车组柴油机恒功率控制技术

柴油机在非恒功率输出时,不仅燃料效率低,而且可能会产生较大的机械应力,导致机械部件的磨损和破坏。为确保内燃动车组柴油机高效运行,基于内燃动车组柴油发电机组恒功率输出的运行模式,文章提出了一种比例-积分控制方法,实现了负载侧牵引系统功率稳定跟随柴油发电机组的输出功率目标值,通过负载侧恒功率运行保障发电机组的恒功率稳定输出,从而提高柴油机燃油经济性。经过仿真及试验测试验证,采用此控制方法,负载功率稳态波动在±2%以内,实现了内燃动车组柴油机恒功率运行及负载功率对目标值的实时跟随。

基于模糊PID的打磨头角度控制策略研究

在进行风电机组叶片表面打磨工序时,需要控制打磨头的径向与叶片表面保持垂直。对打磨头的角度调整问题进行分析和研究,通过分析打磨头的结构构成与运动轨迹,建立打磨头伺服系统的数学模型。基于角度变化引起的重力转矩补偿量,提出一种模糊比例-积分-微分(Proportion-Integral-Differential,PID)的角度伺服控制系统。Simulink仿真验证结果表明,重力补偿后模糊PID控制方法的打磨头伺服系统响应速度更快、误差更小,能够较好地调整打磨头的角度。

基于PI+QPR控制的单相有源电力滤波器研究

补偿电流跟踪控制策略对有源电力滤波器(Active Power Filter,APF)的谐波治理能力有直接影响。在单相系统中,利用并联型APF进行谐波治理时,传统的电流比例积分(Proportional Integral,PI)控制方式具有较快的响应速度,但3次谐波电流不能得到充分抑制。针对这一问题,文中采用准比例谐振(Quasi Proportional-resonant,QPR)控制策略对3次谐波电流进行跟踪控制。同时利用陷波滤波器对ip-iq谐波电流检测算法进行改进,提高谐波电流检测精度,消除数字低通滤波器输出侧直流信号中的低频波动问题。最后通过MATLAB/Simulink建立单相并联型APF谐波治理系统模型,验证了所提控制策略的可行性和有效性。

基于模糊神经网络PID的无人艇航向控制器研究

针对常规比例、积分和微分(proportional integral derivative,PID)控制器在无人艇航向控制系统中表现出的稳定性差、控制精度低等问题,文章提出一种将模糊控制与反向传播(back propagation,BP)神经网络相结合的控制算法;在MATLAB中对比常规PID控制器、模糊PID控制器与模糊神经网络PID控制器在给定期望航向角下的航向控制性能,仿真结果表明模糊神经网络PID控制器对无人艇的航向控制性能最佳;在搭建的实验平台上对不同航向控制器下无人艇的航行轨迹和航向角进行比较,实验结果进一步验证了模糊神经网络PID航向控制算法的优越性。

一种联合PID控制与扩展卡尔曼滤波的磷酸铁锂电池荷电状态估算方法

锂离子电池作为新能源存储的载体,是执行“双碳”目标的重要助力,精确估算电池荷电状态(state of charge,SOC)能够有效辅助电池管理,进而延长电池使用寿命。针对卡尔曼滤波类算法的SOC估算效果受磷酸铁锂电池特性制约的问题,该文提出一种比例积分微分(proportional integral differential,PID)控制与扩展卡尔曼滤波(extended Kalman filter,EKF)联合方法。该方法利用PID控制原理设计SOC初值补偿策略并优化EKF算法的状态变量修正过程,可降低磷酸铁锂电池特性对算法的影响。实验结果表明,与EKF算法相比,所提方法在估算磷酸铁锂电池SOC时拥有更高的估算精度与更快的收敛速度,对电池模型误差与采样噪声表现出较强的鲁棒性。

基于PID控制的自适应密钥生成

在无线安全通信中,生成密钥并保证其稳定是至关重要的。目前绝大多数密钥生成方案都是以恒定的速率探测信道,没有考虑实际环境中由于信道状态的改变而导致信道探测效率和KGR(Key Generation Rate)不稳定的问题。为了使合法通信端的信道探测效率和KGR保持稳定,提出一种基于PID(Proportional Integral Derivative)控制的自适应密钥生成方案。该方案将实际信道探测效率与目标信道探测效率作比较,自适应引入AR(Artificial Randomness),从而保持信道探测效率的稳定;根据反馈的KGR与目标KGR比较,自适应调整信道探测速率,从而保持KGR稳定。仿真结果表明,不论信道环境变化得快与慢,自适应控制器都能将信道探测效率和KGR稳定在相应的目标值附近。

基于PID的陆区航路纵向碰撞风险控制

为提高陆区航路运行的安全性,减少间隔冲突隐患,仿真研究陆区航路纵向碰撞风险,首先,基于位置误差理论建立陆区航路的纵向碰撞风险数学模型,综合考虑飞行员干预时间,使用安全目标水平反推,确定航空器运行安全区域的前后边界;然后,使用Matlab软件的System Identification工具箱拟合辨识快速存取记录器(QAR)数据,得到反映发动机推力手柄角度和速度变化对应关系的传递函数,依此设计比例、积分与微分(PID)控制系统,将航空器纵向间隔控制在安全区域内;最后,使用Simulink搭建控制系统进行仿真,以验证控制系统功能。结果表明:在给定航路流量(50架/h)条件下,该控制系统能够实时计算2机纵向安全间隔范围(3326~16674 m),并在产生间隔冲突时于70 s内将前后机间隔调整至标称值。PID控制系统能够将碰撞风险始终维持在安全目标水平之上,提高航空器运行的安全性。

模糊PID控制下的CSPRs配对进近纵向碰撞风险

为控制近距离平行跑道(CSPRs)配对进近的纵向碰撞风险,提高该程序的运行安全,首先,基于快速存取记录器(QAR)数据分析航空器在进近过程中的速度变化特征,拟合其在进近阶段的定位误差分布;其次,考虑前机的尾流影响,建立基于位置误差的配对进近纵向碰撞风险模型,计算得到前后机的最优纵向间隔;然后,使用Matlab的System Identification工具箱,拟合辨识发动机推力手柄角度和飞机速度变化的相关数据,得到其对应关系的传递函数,根据该函数设计模糊比例、积分、微分(PID)控制系统,通过控制前后机间的纵向间隔使碰撞风险维持在最低值;最后,使用Simulink仿真验证该控制系统。结果表明:模糊PID控制系统在响应时间、超调量、稳定性等方面的表现皆优于传统的PID控制系统,该模糊PID系统能在50 s内将前后机的纵向碰撞风险控制在最低值(1.72×10-38次事故/飞行小时),并且在整个配对程序的实施过程中维持该值。