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.

Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation

In this paper, a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative （FP＋FI＋FD） controller is proposed. It is derived from the conventional parallel proportional-integral-derivative （PID） controller. It preserves the linear structure of a conventional parallel PID controller, with analytical formulas. The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller. Computer simulations are performed to evaluate the performance of the FP＋FI＋FD controller for setpoint tracking and load-disturbance rejection for some complex processes, such as first- and second-order processes with delay, inverse response process with and without delay and higher order processes. Also, the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve. The simulation and real time control is done using National InstrumentTM hardware and software （LabVIEWTM）. The response of the FP＋FI＋FD controller is compared with the conventional parallel PID controller, tuned with the Ziegler-Nichols （Z-H） and /~strSm- H^gglund （A-H） tuning technique. It is observed that the FP＋FI＋FD controller performed much better than the conventional PI/PID controller. Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP＋FI＋FD controller.

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.

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.

A Novel Asymmetric Three-Phase Cascaded 21 Level Inverter Fed Induction Motor Using Multicarrier PWM with PI and Fuzzy Controller

Multilevel inverters are gaining popularity in high power applications. This paper proposes a new ladder type structure of cascaded three-phase multilevel inverter with reduced number of power semiconductor devices which is used to drive the induction motor. The ultimate aim of the paper is to produce multiple output levels with minimum number of semiconductor devices. This paper uses only 11 switches along with 3 diodes and 4 asymmetrical sources to produce an output voltage of 21 levels. The modulation technique plays a major role in commutation of the switches. Here we implement the multicarrier level shifting pulse width modulation technique to produce the commutation signals for the inverter. The proposed multilevel inverter is used to drive the three-phase induction motor. The mathematical modeling of three-phase induction motor is done using Simulink. Furthermore the PI and fuzzy logic controllers are also used to produce the reference waveform of the level shifting technique which in turn produces the commutation signals of the proposed multilevel converter. The controllers are used to control the speed of the induction motor. The effectiveness of the proposed system is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed multilevel inverter works properly to generate the multilevel output waveform with minimum number of semiconductor devices. The PI and fuzzy logic controller performances are evaluated using the results which indicate that with the help of controllers the harmonics has been reduced and the speed control of induction motor is achieved under different loading conditions.

PID-Based Bit Allocation Strategy for Asymmetric Stereoscopic Video Coding with Fuzzy Quality Controller

Asymmetric stereoscopic video coding can take advantage of binocular suppression in human vision by representing one of the two views in lower quality.This paper proposes a bit allocation strategy for asymmetric stereoscopic video coding.In order to improve the accuracy of bit allocation and rate control in the left view,a proportionalintegral-derivative controller is adopted.Meanwhile,to control the quality fluctuation between consecutive frames of the left view,a quality controller is adopted.Besides,a fuzzy controller is proposed to control the variation in quality between the left and right views by comparing the PSNR disparity of two views with a fixed threshold,which is used to quantize the binocular psycho-visual redundancy and adjust the quantization parameter (QP) of the right view correspondingly.The proposed algorithm has been implemented in H.264/AVC video codec,and the experimental results show its effectiveness in rate control while keeping a good quality for the left view,and fewer bits are allocated for the right view so that the overall bit rate is saved by 7.2% at most without the loss of subjective visual quality for stereoscopic video.

Comparative Analysis of Analog and Digital Controllers for Negative Output Superlift Luo Converter (NOSLC)

This paper focuses on the comparative study of analog and digital control techniques for Negative Output Superlift Luo converter (NOSLC). NOSLC is a high gain converter in which the positive source voltage is converted into a negative load voltage. Though the negative load voltage is produced effectively, there is lot of non-linearities that affects the voltage level. To overcome this, analog controllers like Proportional-integral (PI), fuzzy PI and a sliding mode controller (SMC) were proposed for NOSLC. However PI controller does not respond to changes in operating point, fuzzy PI is based on the systematic approach and proved to be a trial and error oriented method and SMC brings an oscillation in the duty cycle. Therefore, to overcome these drawbacks, a digital control technique using PIC microcontroller is proposed in this paper which provides high versatility and programmability approach. Simulation studies are carried out in MATLAB and the performances of these controllers have been investigated for the proposed DC-DC converter. A prototype of the NOSLC converter is built by employing digital control and the results are verified experimentally.

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。

盾构掘进姿态控制技术研究现状与未来展望

为系统地分析我国盾构掘进姿态控制技术的研究进展,基于知网检索到的32篇相关文献,总结盾构掘进姿态的主要表征参数和影响因素,并以盾构液压推进系统为例论述其控制原理。同时,结合盾构姿态智能控制的部分案例,总结PID控制、自适应控制、模糊控制、基于神经网络的控制和基于智能算法的控制等技术的优劣势及应用场景。基于以上分析,对盾构姿态控制技术的发展方向进行展望。研究发现:1)盾构掘进姿态的影响因素主要包括几何参数、地层参数和盾构掘进参数。2)由于盾构推进系统需要同时完成盾构向前推进和姿态调整等复杂任务,因此该系统的参数对盾构姿态有着很大的影响,是姿态控制的关键因素之一。3)相较于传统PID控制方法,智能控制方法与PID控制的结合可以提高系统的响应速度、精度、适应能力和鲁棒性。4)未来研究可以围绕基于多源数据融合的控制算法、构建数据-机制混合驱动的控制技术以及加强控制技术在实际工程中的实用性等方面展开,实现更精准、更高效的盾构掘进姿态控制。

风扰下变质量四旋翼轨迹跟踪控制

针对存在风扰和变质量负载扰动的四旋翼无人机轨迹跟踪控制问题,提出了一种基于降阶广义比例积分观测器的动态面模糊滑模控制方法。首先,建立含风扰和变质量负载扰动的四旋翼无人机系统模型;其次,结合四旋翼无人机系统模型设计降阶广义比例积分观测器估计外界风扰;再次,设计动态面滑模控制器,并采用模糊控制模糊化切换增益,以此有效地抑制抖振;然后,通过Lyapunov稳定性证明四旋翼无人机系统的稳定性;最后,通过Matlab-Simulink进行3种控制方法的仿真比较。仿真结果表明,当存在风扰和变质量负载扰动时,该控制方法抗风扰能力更强,稳定性更好,位姿跟踪精度更高。

低附着路况条件下车辆横向稳定性控制

针对在冰雪环境下车辆横向稳定控制,为解决在低附着、分布不均的路面情况下车辆对参考轨迹的稳定跟踪问题,设计了基于神经网络调节的模糊PID(Proportional-Integral-Differential)制器,以及基于线性化车辆模型的模型预测控制(MPC:Model Predictive Controll)。以路面附着系数及车辆速度作为输入构建BP(Back-Propagation)神经网络,输出调节系数优化模糊PID控制器控制性能;设计了十自由度模型表征车辆在冰雪环境下的动力学特性,使用MPC实现车辆横向稳定控制。使用CarSim/Simulink进行联合仿真实验,结果表明该控制器能显著提高车辆轨迹跟踪性能。

磁力馈能主动悬架稳定性分析

为了提高车辆行驶平顺性和安全性,提出了一种新型磁力馈能主动悬架,并研究其稳定性。采用BP神经网络PID控制算法(BP-PID)搭建磁力馈能主动悬架控制系统,利用MATLAB/Simulink进行理论仿真。建立B级和C级随机路面,仿真分析不同速度、不同等级下,磁力馈能主动悬架的稳定性。结果表明,相比于被动悬架效果和PID控制的磁力馈能主动悬架效果,采用BP-PID控制可明显提高悬架稳定性。B级随机路面60 km/h时车身垂直加速度改善了45.90%,证明了BP-PID控制的合理性,可有效提升悬架稳定性。

集成式电子液压线控制动系统建模与仿真

为了解决线控制动系统模型复杂、仿真困难等问题,文章针对一款常见的集成式电子液压线控制动(integrated electronic hydraulic brake,I-EHB)系统,推导其数学模型并进行仿真分析;在MATLAB/Simulink中搭建线控制动系统的仿真模型,设计比例积分微分(proportion integration differentiation,PID)制动控制器,实现对集成式电子液压线控制动系统的压力控制。仿真结果表明:该线控制动系统在PID控制器作用下实际输出压力值能够较好地跟随理想压力值,可以提供较好的制动效果。该文的研究对于线控底盘的开发具有积极推动作用。

输电线路清障飞行机器人双行走轮同步控制

传统架空输电线路异物清除作业无人机易受环境影响,作业困难且存在较多扰动等问题。基于此本文设计一种高空作业无人机挂线行走控制机构解决该问题。首先,根据输电线路环境与无人机作业模式,设计挂线行走机构,减弱高空作业时对无人机所受飞行作业扰动的影响;其次,针对清障机器人双行走轮转速同步存在误差问题,提出一种基于反向传播–比例积分微分(back propagation-proportional-integral-differential,BP-PID)主从融合偏差耦合的电机同步控制策略。通过仿真与实物实验验证表明,本文提出的挂线作业无人机双行走轮同步控制算法可有效解决电机因负载导致的转速不稳定以及高空作业无人机受环境扰动的问题。

闭链级混联式液压机械臂运动控制方法

针对含有多个闭链结构的液压机械臂非线性强、控制精度低等特点,采用了虚拟分解控制方法消除了系统非线性引入的误差,以提高其控制精度。首先,根据驱动方式不同将整个机械臂分解为四类结构,针对每一类结构再将其虚拟分割成每一子系统,对每个子系统分别建立了刚体动力学模型、液压执行器流体动力学模型;然后,基于刚体动力学模型和流体动力学模型分别设计了刚性连杆控制律和液压执行器控制律,其前馈控制量和误差反馈量是高精度控制的基础;最后,使用Simulink的Simscape模块建立了该机械臂的多物理域混合模型,进行了轨迹跟踪效果验证,同时引入了控制性能指标,在不同机械臂的液压执行器空间进行了计算。研究结果表明:相比于比例-积分-微分控制器,基于虚拟分解控制理论搭建的控制器控制精度提升较大,单关节平均绝对误差最大降低了88.9%,且控制效果与其他较先进液压控制器的性能指标相近。针对含复杂闭链结构的混联式液压机械臂,采用虚拟分解控制理论能有效提升控制精度。

基于混沌粒子群优化算法的反应釜温度预测控制研究

反应釜作为化工行业核心的生产容器,其温度控制优化在化工生产领域中具有重要作用。针对反应釜温度控制难的问题,提出了一种基于Tent映射的混沌粒子群优化(CPSO)算法优化动态矩阵控制(DMC)-比例积分微分(PID)的反应釜温度预测控制策略。由于DMC很难选取较优的参数,利用Tent映射的CPSO算法提高动态矩阵参数寻优的速度。通过试验,以及与常规PID、DMC-PID控制对比分析,基于Tent映射的CPSO-DMC-PID串级控制对温度控制系统有较好的控制精度和响应速度,可大幅缩小超调量。该控制策略对反应釜温度预测控制研究具有一定的参考意义。

剖面浮标变体积油囊式浮力调节系统设计

为精准控制剖面浮标的垂向运动,提出一种可精确控制油量的变体积油囊式浮力调节系统,包含外油囊、增压油箱、密封性能良好的电磁球阀和可调节转速的液压泵等组件。采用拉线位移传感器实时采集增压油箱液面位置实现油量监控,并对外油囊体积进行高精度闭环反馈控制;设计极低泄漏量的液压系统,实现系统在待机状态下浮力保持长期稳定。为精确控制浮力调节系统,构建控制系统数学模型,引入比例积分微分(Proportional Integral Differential,PID)控制算法,并采用Simulink进行稳定性仿真。试验结果表明,系统可实现浮力精确控制,最大超调量低于1%,稳定性与响应速度均符合预期,验证了控制策略的可靠性。

基于BP神经网络的Fuzzy-PID恒温控制器

在高精度恒温系统温度控制中,为了克服温度这种被控对象因其纯滞后、非线性和大惯性特性以及被控对象参数的时变性对精度的影响,采用了BP神经模糊PID控制器代替模糊控制,使推理速度加快,并通过在系统运行时不断地增加和完善模糊控制规则,不断提高系统控制的精度。仿真分析结果表明,经过BP神经网络优化学习后,系统具有良好的控制性能和自适应能力,很好地满足了大滞后系统对高精度控温与快速性的要求。

三相升-降压PWM整流器Fuzzy-PI控制算法

针对直流电机控制等应用领域对大范围连续平滑可调直流电压的需求,分析了现有升-降压整流系统的不足,基于三相电压型升-降压PWM整流器的工作原理,按照有效降低开关损耗、控制简单、易于工程实现等原则,用拓展零矢量对传统SVPWM控制策略进行改进,建立了相应的数学模型,进行了相应的数学分析,设计了自适应模糊控制和PI控制相结合的双模控制方案,并通过Matlab7.11环境下的离散化模型仿真,将新控制算法与已有控制算法比较,证明了新控制算法的良好效果。