A Novel Sliding Mode Variable Structure Controller Based on a Genetic Algorithm

A novel control method has been proposed by using the genetic algorithm （GA） for nonlinear and complex plants. The proposed control strategy is based on a variable structure control, it overcomes the defects of other adaptive methods such as strong dependence to the system. A GA is used to learn to optimally select integral coefficient C. Simulation results verified the effectiveness of the controller. For position control of Direct Current （DC） motor in practice, this method has good performance and strong robustness, and both dynamic and steady performances were improved.

Optimization of MAC algorithm based on IEEE 802.15.4 in indoor positioning system

The mobility of the targets asks for high requirements of the locating speed in indoor positioning systems.The standard medium access control(MAC)algorithm will often cause lots of packet conflicts and high transmission delay if multiple users communicate with one beacon at the same time,which will severely limit the speed of the system.Therefore,an optimized MAC algorithm is proposed based on channel reservation to enable users to reserve beacons.A frame threshold is set to ensure the users with shorter data frames do not depend on the reservation mechanism,and multiple users can achieve packets switching with relative beacon in a fixed sequence by using frequency division multiplexing technology.The simulation results show that the optimized MAC algorithm proposed in this paper can improve the positioning speed significantly while maintaining the positioning accuracy.Moreover,the positioning accuracy can be increased to a certain extent if more channel resources can be obtained,so as to provide effective technical support for the location and tracking applications of indoor moving targets.

Fuzzy logic algorithm of hovering control for the quadrotor unmanned aerial system

Purpose–The purpose of this paper is to present a control strategy which uses two independent PID controllers to realize the hovering control for unmanned aerial systems(UASs).In addition,the aim of using two PID controller is to achieve the position control and velocity control simultaneously.Design/methodology/approach–The dynamic of the UASs is mathematically modeled.One PID controller is used for position tracking control,while the other is selected for the vertical component of velocity tracking control.Meanwhile,fuzzy logic algorithm is presented to use the actual horizontal component of velocity to compute the desired position.Findings–Based on this fuzzy logic algorithm,the control error of the horizontal component of velocity tracking control is narrowed gradually to be zero.The results show that the fuzzy logic algorithm can make the UASs hover still in the air and vertical to the ground.Social implications–The acquired results are based on simulation not experiment.Originality/value–This is the first study to use two independent PID controllers to realize stable hovering control for UAS.It is also the first to use the velocity of the UAS to calculate the desired position.

Application of Artificial Neural Network in Robotic Hybrid Position/Force Control

A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environment and can optimize the parameters of PIDcontroller.The experimental results show that after having been trained,the robot has sta-ble response to the training patterns and strong adaptive ability to the situation between thepatterns.

Algorithm of Attitude Control and Its Simulation of Free-Flying Space Robot

Reaction wheel or reaction thruster is employed to maintain the attitude of the base of space robot fixed in attitude control of free flying space robot. However, in this method, a large amount of fuel will be consumed, and it will shorten the on orbit life span of space robot, it also vibrate the system and make the system unsteady. The restricted minimum disturbance map (RMDM) based algorithm of attitude control is presented to keep the attitude of the base fixed during the movement of the manipulator. In this method it is realized by planning motion trajectory of the end effector of manipulator without using reaction wheel or reaction thruster. In order to verify the feasibility and effectiveness of the algorithm attitude control presented in this paper, computer simulation experiments have been made and the experimental results demonstrate that this algorithm is feasible.

基于位置式PID的水暖床垫温度控制系统设计

温度控制在生产生活中发挥着举足轻重的作用。位式控制算法在调节具有滞后性的水暖床垫温度控制系统时容易导致温度在目标值上下波动,控制效果不理想。为了解决此问题,设计了一种基于位置式PID的水暖床垫温度控制系统,系统以51内核的微处理器为核心控制器、以负温度系数热敏电阻(Negative Temperature Coefficient,NTC)为温度传感器、以PTC为加热器、以直流电机作为循环水泵。经实际测试结果表明,该系统运行稳定,控温精度在±0.5℃以内,达到了理想的温度控制效果。

基于灰狼算法的步进电机滑模控制系统设计

为了改善转台方位轴的位置精准度及抖振现象,本文围绕步进电机控制系统展开研究。设计了指数趋近律的位置方程,应用了灰狼优化算法整定滑模控制系统的多项参数。在此基础上建立了数学模型,使用MATLAB/Simulink构建了位置三闭环仿真,对系统的位置精准度、抗干扰能力进行分析,并与PID控制系统、传统的滑模控制系统进行了比较。仿真结果表明优化后的控制系统较稳定,响应速度快,抗干扰能力强。最后基于STM32F10ZET6主控芯片搭建了硬件平台,实验证明了优化后的控制策略有效提升了位置精准度,保证了系统的可靠性。

基于参数自适应DBSCAN算法的浮标位置数据异常检测

针对遥测遥控系统采集浮标位置数据时易受外在因素的干扰,提出了一种K近邻优化的参数自适应DBSCAN算法,来检测浮标位置数据中的异常点。通过分析数据集的分布特性生成最优邻域距离值ε和邻域内样本点数量MinPts列表,引入卡林斯基-哈拉巴斯指数对列表中的参数进行评分,将最高评分对应的参数作为最优参数,实现DBSCAN算法的自适应聚类。实验结果表明,新算法能够自适应选择最优参数,对浮标遥测位置数据的异常点进行有效检测。

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。

建筑起重机变幅液压缸位置ACO优化PID控制优化

为了提高建筑起重机变幅液压缸位置控制精度,引入蚁群算法(Ant Clony Optimization,ACO)对PID控制进行优化,给出了位置控制系统控制器。并针对阶跃响应和正弦响应,开展仿真分析。得到如下结论:处于干扰力阶跃响应下,蚁群算法相对Ziegler-Nichols与果蝇算法(Fruit Flies Optimization,FFO)优化PID控制系统响应曲线分别减小了32.1%与12.3%的超调量,调整时间缩短34.3%与26.54%,稳态误差减小54.18%与33.21%。利用ACO优化PID系统表现出了更优的阶跃响应性能。处于干扰力正弦响应下,以ACO优化PID系统相对其它两种算法获得了更低的最大跟踪误差,时平均跟踪误差也明显减小。经综合分析可知,采用ACO优化PID系统获得了最优的抗干扰性能。该研究对提高起重机变幅液压缸位置控制精度具有很好的实际指导意义。

模块化蛇形机器人运动控制系统研究

近年来,人工智能技术得到了广泛的应用和发展,其中机器人技术已经取得了长足进步。而蛇形机器人因其高度仿真的蛇形动态及运动特性而备受瞩目。以锥齿传动结构蛇形机器人为载体,以STM32为主控制器,采用开环控制和闭环控制相结合的方式控制其运动,通过位置式PID控制算法解算装置姿态,提出一种适用于蛇形机器人灵活运动的控制算法。

Simulating unmanned aerial vehicle flight control and collision detection

An unmanned aerial vehicle(UAV)is a small,fast aircraft with many useful features.It is widely used in military reconnaissance,aerial photography,searches,and other fields;it also has very good practical-application and development prospects.Since the UAV’s flight orientation is easily changeable,its orientation and flight path are difficult to control,leading to its high damage rate.Therefore,UAV flight-control technology has become the focus of attention.This study focuses on simulating a UAV’s flight and orientation control,and detecting collisions between a UAV and objects in a complex virtual environment.The proportional-integral-derivative control algorithm is used to control the orientation and position of the UAV in a virtual environment.A version of the bounding-box method that combines a grid with a k-dimensional tree is adopted in this paper,to improve the system performance and accelerate the collision-detection process.This provides a practical method for future studies on UAV flight position and orientation control,collision detection,etc.

基于TI TM4C123的激光追踪系统设计

针对激光目标追踪易丢失、实时性差的问题,该文设计基于德州仪器的TM4C123芯片作为主控的激光目标控制系统与自动追踪,V831摄像头模组作为目标位置反馈测量装置,以二维闭环步进电机云台作为运动输出。摄像头模组通过串口与TM4C主控通信实时反馈目标点位置,使用PID控制算法控制电机输出。同时通过磁编码反馈防止步进电机丢步,实现位置闭环控制,实验结果表明,系统追踪精度高,实时性好。

计算机数据融合算法下植保机精准化作业研究

针对我国传统的植保机在精准化作业和自动化喷洒方面存在的不足,基于计算机数据融合算法对植保机精准化作业进行了设计试验。植保机的主要组成包括控制单元模块、信息采集模块、传感器模块、数据传输模块和变量执行器模块。为了实现植保机的精准化作业,对植保机的飞行姿态调整和变量喷药过程进行了算法设计。其中,飞行姿态控制采用双闭环位置式PID控制算法,喷药过程采用改进的遗传PID控制算法进行控制。为了验证植保机精准化作业的效果,对其进行姿态控制和变量喷药试验。结果表明:植保机姿态控制良好,能够完成精准化喷药。

微型涡旋压缩机轴向力曲线匹配吸力足机构优化研究

微型涡旋压缩机的轴向气体力随主轴转角而大幅度变化,存在难以实现良好的轴向密封等问题,为此,提出了一种基于永磁体的轴向磁力平衡轴向气体力的吸力足机构。首先,对微型涡旋压缩机的轴向气体力进行了特性分析,确定了目标轴向气体力曲线;其次,基于JMAG建立了三维仿真模型,采用遗传算法对永磁体的位置进行了优化,由此达到了轴向力变化趋势最大的目标;再次,在永磁体位置优化基础上,提出并对比了4种不同的吸力足分块方案,改变了分块吸力足的高度来匹配随动涡盘平动而变化目标的轴向力曲线;最终,对选择方案的分块吸力足高度敏感性进行了分析,固定了敏感性低的分块高度,降低了实际制作和装配的复杂性;通过仿真和实验测试,对优化后吸力足机构轴向力的准确性进行了验证。研究结果表明:改变永磁体在静环的位置,轴向力的最大值提升27.56%;在所有分块方案中,分块数越多,吸力足机构平衡效果越佳,且周向切割优于径向切割,周向切割最优结构的积分差相较于径向切割方案减小了42.91%;经实验验证后,优化的吸力足机构的最大误差仅为6.2%,与仿真结果具有良好的一致性,很大程度上解决了微型涡旋压缩机的轴向密封问题。

基于滑膜观测的FOC无刷电机控制系统设计

针对目前全驱动型机器人的高工作精度以及高稳定性需求,设计全驱动型机器人关节驱动控制系统。基于无刷电机数学模型,电机驱动方案采用矢量电机控制算法FOC,电机角速度位置采用有感、无感相结合获取,即在启动以及低速转动下采用位置传感器,在中高速转动下切换使用滑模观测器。观测器对电机反电动势观测值进行运算处理,获得电机位置和速度。在MATLAB/Simulink搭建控制模型,验证算法可行性。仿真结果表明:在负载情况下,中低转速下,控制精度低,低成本位置传感器足以满足控制需求;在中高转速下,位置获取方法切换为滑模观测器,此时无位置传感器控制,无需使用高精度位置传感器,根据电机运行的电流观测到的位置,足以满足中高转速需求。且观测器监测内部运行状态,无视外界影响,大大提高控制系统的响应性与稳定性。

PLC对伺服电机的精准定位控制研究

采用可编程逻辑控制器(Programmable Logic Controller,PLC)与编码器、控制算法相结合的方式对伺服电机进行精准定位控制,研究控制技术和硬软件配置对定位精度的影响。通过优化编码器选型、算法设计及软硬件编程,可进一步提高定位精度和控制灵活性,满足不同应用需求。采用PLC可有效提高伺服电机的定位精度,提升自动化生产的加工精度和效率。综合响应特性、可编程性及适用范围等因素,PLC具有广阔的应用前景,将在智能制造中发挥重要作用。

Implementation of Mooring Automatic Positioning System for Deepwater Semi-Submersible Platform Based on Dual-Stage Actuator

The automatic positioning control of mooring system for deepwater semi-submersible platform has become a key issue in the research and development field of deep-sea resources. The Dual- Stage Actuator (DSA) proposed in this paper can replace the single actuator to achieve the high speed and high precision positioning by cooperative control. The relative model and control algorithm of motion trajectory (CAMT) are designed and validated, which proves that the method proposed in this paper is effective.

挖掘机铲斗电液伺服改进PSO-PID参数整定位置控制

挖掘机电液伺服系统的运行性能来达到调控挖掘机铲斗位置的功能,由于采用传统PID整定方法并不能获得优异控制效果,采用遗传算法与交叉算子、标准PSO算法进行PID整定,最后对其进行了实验验证。设计了一种经过改进处理的粒子群优化算法来实现对阀挖掘机铲斗电液伺服系统进行PID整定的过程,能够准确控制挖掘机铲斗位置,由此获得更高轨迹跟踪精度。为增强粒子群算法搜索性能,综合运用遗传算法与交叉算子来实现对标准粒子群的优化,显著改善PID控制器性能,根据推导得到的铲斗系统模型进一步开展仿真分析。分别以三种优化算法计算优化结果,再将其输入自动化挖掘机程序中,完成各参数修改后,再对平地控制过程进行模拟测试。根据实验测试可知改进PSO算法具备明显优越性。

基于在线差分进化算法的平面开关磁阻电机约束预测位置控制

模型预测控制方法在解决平面开关磁阻电机非线性、不确定干扰、约束等问题具有突出的优势,有望实现平面开关磁阻电机的高精度约束最优控制,目前平面开关磁阻电机约束预测控制亟需解决在线计算量大、内存大的问题。为快速、精确地求解平面开关磁阻电机约束预测控制在线优化问题,并获得小内存控制器,提出基于在线差分进化算法的约束预测位置控制方法。基于电机的多步预测位置模型,建立考虑输入约束的电机预测位置控制器,采用设计的差分进化算法在线求解最优控制量,构建具有摩擦补偿的电机约束预测位置控制系统。为提高差分进化算法的收敛速度并获得更优解,采用缩小种群范围、生成分区种群个体以及优化初始种群的操作产生初始种群,利用优化的变异因子和交叉因子对种群个体进行变异和交叉操作,将预测控制的代价函数作为适应度函数对种群个体进行选择操作。仿真和实验结果验证了所提方法的有效性。