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.

Conventional and Added-Order Proportional Nonlinear Integral Observers

In this paper, a kind of fire new nonlinear integrator and integral action is proposed. Consequently, a conventional Proportional Nonlinear Integral (P_NI) observer and two kinds of added-order P_NI observers are developed to deal with the uncertain nonlinear system. The conditions on the observer gains to ensure the estimated error to be ultimate boundness, which shrinks to zero as the states and control inputs converge to the equilibrium point, are provided. This means that if the observed system is asymptotically stable, the estimated error dynamics is asymptotically stable, too. Moreover, the highlight point of this paper is that the design of nonlinear integral observer is achieved by linear system theory. Simulation results showed that under the normal and perturbed cases, the pure added-order P_NI observer can effectively deal with the uncertain nonlinearities on both the system dynamics and measured outputs.

Analysis and Experimental Study of Proportional-Integral Sliding Mode Control for DC/DC Converter

DC/DC converter using the proportional-integral (PI) sliding mode control (SMC) scheme is investigated, including the selection of the switching surface, the proof of the reaching condition and the existence condition of sliding motion. The sliding regime and the local stability are given. The implementation of the PI SMC is simpler than other SMC schemes and the steady-state error is eliminated. A prototype based on Buck converter is built up. The experimental results show that the dynamic performance and robustness to the parameter variations and external disturbances are improved.

Robust Fractional-Order Proportional-Integral Observer for Synchronization of Chaotic Fractional-Order Systems

In this paper, we propose a robust fractional-order proportional-integral(FOPI) observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities(LMIs) approach by using an indirect Lyapunov method. The proposed FOPI observer is robust against Lipschitz additive nonlinear uncertainty. It is also compared to the fractional-order proportional(FOP) observer and its performance is illustrated through simulations done on the fractional-order chaotic Lorenz system.

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.

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。

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。

引入PID反馈的SHAEKF算法估算电池SOC

电池荷电状态(SOC)的估算精度是电动汽车电池组的重要指标。为提升SOC估算精度,在融合Sage-Husa扩展卡尔曼滤波(SHEKF)算法与自适应扩展卡尔曼滤波(AEKF)算法的基础上,增加比例积分微分(PID)反馈环节,形成改进算法。采用粒子群优化(PSO)算法对二阶RC等效电路模型进行参数辨识;用开源电池数据集对模型和算法进行实验和分析。改进的SHAEKF算法在电池动态应力测试(DST)、北京动态应力测试(BJDST)和美国联邦城市驾驶(FUDS)等工况下的平均估计误差都在1%以内,与单纯的融合算法SHAEKF算法相比,最大误差可减小5%。

基于金豺优化PID的直流电机调速控制系统

针对传统直流(DC)有刷电机调速系统适应性不强、抗干扰能力和稳健性差等缺点,设计了基于金豺算法优化比例-积分-微分(PID)的直流有刷电机控制系统.在建立电机数学模型的基础上,将金豺优化(GJO)算法应用于PID参数整定,实现对电机的控制,并分别与传统试凑法、反向传播(BP)-PID算法和麻雀算法(SSA)-PID进行对比.仿真结果表明:所设计的控制算法在调节时间上减少了12 ms,超调量降低了3.689%,受到干扰后的调节时间减少了17 ms,表现出更快的调节转速、更强的抗干扰能力和更好的稳健性,为直流有刷电机调速控制提供了一种有效的方案.

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.

Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.

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。

基于MPC和PID的脚轮式全向移动平台轨迹跟踪

针对现有运动控制策略无法保证独立驱动脚轮式全向移动平台位姿的高精度控制问题,提出一种基于模型预测控制(MPC)和PID控制相结合的双闭环轨迹跟踪控制策略。首先,利用运动学几何关系建立独立驱动脚轮式全向移动平台在世界坐标系下的三自由度运动学模型,基于正交分解法建立平台在机器人坐标系下的逆运动学模型,以反映平台中心点速度与各个脚轮转速间的关系;其次,采用MPC并基于三自由度运动学模型设计位姿控制器,使平台对期望轨迹进行位姿跟踪,并在考虑多目标约束条件的情况下通过位姿控制器求解出最优控制量;最后,采用PID设计速度控制器,用于跟踪位姿控制器输出的期望速度,通过平台逆运动学模型计算得到期望轮速,从而驱动平台实现全向运动。通过仿真验证了所提控制策略的有效性,平台能有效跟踪直线轨迹和圆形轨迹。仿真结果表明,与通过平台转角逆运动学模型解耦驱动轮速的位置单环轨迹跟踪控制策略相比,加入速度内环后系统超调量下降97.23%,响应时间缩短36.84%。

永磁同步电机抗积分饱和PI控制研究

永磁同步电机矢量控制中传统PI控制器在给定输入发生较大幅度变化造成积分项逐渐累加,引起积分饱和,从而使转速及转矩超调,系统调节变缓,控制系统控制性能降低。针对这一问题,在传统PI控制基础上提出了一种抗积分饱和PI控制控制策略,将该控制策略分别应用到永磁同步电机速度环和电流环PI控制中。为验证该控制策略的有效性,基于MATLAB/Simulink仿真平台构建了永磁同步电机抗积分饱和PI控制系统仿真模型。仿真实验结果表明,与传统的PI控制算法相比较,所构建抗积分PI控制模型系统超调量明显降低,能够快速到达稳态,具有较好的动态性能和抗干扰能力。

基于改进PID-LQR的导弹稳定控制方法研究

导弹稳定控制系统是提高导弹制导性能的关键技术之一,一直以来都是研究的热点和重点。以导弹纵向平面为例,建立了导弹稳定控制的状态空间模型,推导了LQR控制算法,在传统LQR方法的基础上,结合PID算法提出了一种改进的PID-LQR导弹稳定控制方法。通过仿真分析,比较了所提方法和传统LQR方法、改进LQR方法、模糊PID-LQR方法的控制性能,并对建立的导弹模型参数进行了拉偏试验,仿真结果表明所提出的方法优于其他3种方法,具有良好的控制性能和鲁棒性。