基于模糊PID算法的车载液压调平动态特性联合仿真研究

基于车载平台液压调平系统,为了减少支腿的跟踪误差及其同步误差,降低支腿之间的运动耦合,采用模糊PID控制算法实现调平过程中动态特性控制。利用AMESim和MATLAB/Simulink分别建立调平液压回路和模糊PID控制器的仿真模型并进行联合仿真研究。结果表明,加入模糊PID算法比常规PID算法能够有效的减少支腿的跟踪误差和定位误差以及支腿之间同步误差,有效提高调平精度。     

高速开关阀控气动位置伺服系统的模糊自适应PID控制

为实现高速开关阀控气动位置伺服系统的精确控制,以4个高速开关阀控制气缸的结构作为研究对象,提出一种模糊自适应PID算法以提高其控制精度.介绍了系统的结构与工作原理,并在此基础上建立系统数学模型.针对常规PID控制器难以适应多工况位置跟踪的问题,利用模糊控制原理对PID控制器的参数进行在线调整,以满足系统控制过程中对于参...     

基于模糊PID控制的起爆具生产线温度控制系统

为了提高起爆具生产线中浇注锅温度的控制精度,以提高起爆具产品的质量,分析了起爆具生产线中浇注锅温度控制系统的组成,将模糊控制和常规PID控制结合起来,设计出了模糊PID控制器,通过以往对浇注锅温度控制的经验,制定出了PID 3个参数的模糊控制规则表,最后将模糊PID控制算法通过可编程逻辑控制器（PLC）编程来实现;在Matlab中的Simulink工具箱里搭建了模糊PID控制器和常规PID控制器模型,并对这两个控制器进行了仿真比较.研究结果表明,相对于常规PID控制器,模糊PID控制器具有更好的调节精度.该系统在生产线中的实际运用结果显示,模糊PID温度控制器效果较好,达到了预期的温度控制要求;系统适用于起爆具生产线中浇注锅的温度控制,对提高起爆具产品质量和生产效率具有一定的意义.     

A Self-Organising Fuzzy Logic Controller for a Coordinate Machine

For a 3D coordinate measurement system, the dynamic accuracy of the moving table will influence the measuring accuracy directly. If a classical PID controller were designed for this measuring table without an accurate mathematical model, the gain parameters may need to be regulated frequently by trial-and-error to obtain the precise motion control objective, good adaptability, and robustness. In this paper, a model-free fuzzy controller and a self-organising fuzzy controller (SOFC) were employed to eliminate the above controller design problems and improve the tracking control accuracy. The control performances of these intelligent control strategies were compared, based on the experimental results. The SOFC has the best tracking accuracy and its learning ability significantly reduces the trial-and-error design effort of a traditional fuzzy controller.     

基于变模糊PID控制器的阀控非对称缸复合控制策略

针对非对称液压缸正反向运动的不对称性对位移控制精度的影响,为了提高阀控非对称液压缸伺服系统位移控制精度,设计了根据液压缸运动方向选择对应模糊PID位移控制器的位移闭环及速度前馈复合控制方案。搭建了基于ADAMS,AMESim和Simulink的阀控非对称液压缸伺服系统联合仿真模型。研究表明,采用速度前馈控制系统响应更快;采用对应变模糊PID位移控制器控制策略,非对称缸换向跟踪期望位移的精度更高。     

超磁致伸缩致动器的小脑神经网络前馈逆补偿-模糊PID控制

针对超磁致伸缩致动器(GMA)在精密致动控制中存在的迟滞和位移非线性,提出了小脑神经网络(CMAC)前馈逆补偿结合模糊PID控制的新策略。通过小脑神经网络(CMAC)学习获得超磁致伸缩致动器动态逆模型用于对超磁致伸缩致动器迟滞非线性进行补偿;利用模糊PID控制降低小脑神经网络(CMAC)学习时的误差和抑制扰动,提高系统的跟踪控制性能,从而实现超磁致伸缩致动器的精密致动控制。仿真和实验结果表明:所采用的控制策略有效地消除了迟滞非线性的影响,系统的跟踪误差降低到了5%以下,而位移跟踪误差均方差仅为0.58。此外,这种策略的特点是学习和控制同时进行,控制系统能够适应被控对象动态特性的变化,使系统具有较强的鲁棒性,同时也能够有效地抑制外界的干扰,提升系统的自适应控制性能。     

Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload

The interval type-2 fuzzy logic controller (IT2-FLC), with footprint of uncertainty (FOU) in membership functions (MF), has increasingly recognized for controlling uncertainties and nonlinearities. Within the ambit of this, the efficient interval type-2 fuzzy precompensated PID (IT2FP-PID) controller is designed for trajectory tracking of 2-DOF robotic manipulator with variable payload. A systematic strategy for optimizing the controller parameters along with scaling factors and the antecedent MF parameters for minimization of performance metric integral time absolute error (ITAE) is presented. Prominently, recently proposed optimization technique hybridizing grey wolf optimizer and artificial bee colony algorithm (GWO–ABC) is utilized for solving this high-dimensional constrained optimization problem. In order to witness effectiveness, the performance is compared with type-1 fuzzy precompensated PID (T1FP-PID), fuzzy PID (FPID), and conventional PID controllers. More significantly, the robustness of IT2FP-PID is examined for payload variation, model uncertainties, external disturbance, and noise cancellation. After experimental outcome, it is inferred that IT2FP-PID controller outperforms others and can be referred as a viable alternative for controlling nonlinear complex systems with higher uncertainties.     

Neural network controller for robotic motion control

Since a robotic manipulator has a complicated mathematical model, it is difficult to design a control system based on the complicated multi-variable nonlinear coupling dynamic model. Intelligent controllers using fuzzy and neural network approaches do not need a real mathematical model to design the control structure and have attracted the attention of robotic control researchers recently. A traditional fuzzy logic controller does not have learning capability and it needs a lot of effort to search for the optimal control rules and the shapes of membership functions. Owing to the time-varying behaviour of the system, the required fine tracking accuracy is difficult to achieve by adjusting the fuzzy rules only. The implementation problems of neural network control are the initial training and initial transient stability. In order to improve the position control accuracy and system robustness for industrial applications, a neural controller is first trained off-line by using the input and output (I/O) data of a traditional fuzzy controller. Then the neural controller is implemented on a five-degrees-of-freedom robot with a back propagation algorithm for online adjustment. The experimental results show that this neural network controller achieved the required trajectory tracking accuracy after 15 on-line operations.     

滚珠丝杠传动机构的微动特性及轨迹跟踪控制

滚珠丝杠传动的机床进给机构在微观运动条件下的各种非线性因素和进给系统较高的机械增益是影响机床运动的控制精度进一步提高的主要因素.本文研究了滚珠丝杠进给机构的微动特性,结果表明库仑摩擦和微弹性现象是滚珠丝杠在微动条件下的主要运动特性.针对这一特性,提出了一种基于误差的增益自适应控制器,该控制器能够有效地提高系统的稳定性,并能保证足够的控制精度.对幅值为1μm的正弦输入,其跟踪控制误差小于0.04μm.对幅值为1mm的正弦输入,其跟踪控制误差为0.5μm.     

一种仿章鱼腕足柔性模块的设计与运动控制

针对软体机器人由于刚度太低且是连续变形,故很难进行运动控制的问题,提出一种由形状记忆合金弹簧驱动的柔性机械臂。机械臂由３Ｄ打印制造而成,内部嵌入３个线性霍尔传感器,用于测量柔性臂弯曲运动。通过压缩补偿计算可以精确控制弯曲运动。实验结果表明,该柔性机械臂可以以较高精度进行三维运动。     

轮式移动机器人轨迹跟踪控制算法的研究

为解决轮式移动机器人平面运动控制问题,将平面几何理论应用于轨迹跟踪控制中。建立了机器人平面运动模型,并以此为基础研究了直线和圆弧的轨迹跟踪控制算法;提出了导航圆方法,将机器人实时位置信息和目标轨迹之间的角度偏差及位置偏差综合成一个角度,然后对该角度进行了PID调节;在实验中,将直线、圆弧轨迹跟踪算法实际运用于机器人的运动控制。研究结果表明,该算法能将机器人轨迹的偏差有效地控制在±1 cm以内。     

基于PMAC的码垛机器人模糊PID算法研究

为了提高可编程多轴运动控制器(PMAC)的控制精度和性能,设计了模糊PID控制算法.该算法应用在4自由度码垛机器人控制系统中,通过机器人电机在传统PID控制下与模糊PID控制下的位置阶跃响应实验和速度抛物线响应实验,利用电机的调节时间Ts、超调量Mp、上升时间T r、最大跟随误差M feer等数据证明模糊PID控制算法很好地改善了机器人控制系统的稳定性,提高了伺服电机的稳态性能和动态性能,改善了PMAC对4自由度码垛机器人的控制效果.     

Variable structure fuzzy control using three input variables for reducing motion tracking errors

Conventional fuzzy controllers for motion tracking utilize generally two input variables (position error and velocity error) to deal with highly nonlinear and time-varying dynamics associated with complex mechanical motion with multi- DOF. This results in some tracking errors at steady state, in general, mainly due to friction existing in mechanical systems. To eliminate the steady-state tracking errors, a variable structure fuzzy control algorithm is proposed using three input variables (position error, velocity error, and integral of position errors) and a switching logic between two inputs and three inputs. Simulation and experimental studies have been conducted to show the validity of the proposed control logic using a direct-drive SCARA manipulator with two degree-of-freedom. It has been shown that the proposed fuzzy control logic has significantly improved motion-tracking performance of the mechanical system when it is applied to complex polygon-tracking in Cartesian space with inverse kinematics and path planning. This paper was recommended for publication in revised form by Associate Editor Kyongsu Yi Chul-Goo Kang received his B.S. and M.S. degree in Mechanical Design and Production Engineering from Seoul National University, Korea, in 1981 and 1985, respectively. He then received his Ph.D. degree from Univ. of California, Berkeley in 1989. Dr. Kang is currently a Professor at the Department of Mechanical Engineering, Konkuk University in Seoul, Korea. He serves as a board member of the Institute of Control, Robotics and Systems, and also Korea Robotics Society. His research interests include motion and force control, train brakes, and intelligent robots.     

电液比例位置控制系统Fuzzy-PID控制的应用

针对电液比例阀控缸位置控制系统实时性能差和具有严重时变性的特点,设计了一种新型PID控制算法,并将该算法与模糊控制相结合构成Fuzzy-PID控制,对其在电液比例位置控制系统上的应用进行研究。通过实验比较不同工况下该系统Fuzzy-PID控制和常规PID控制对正弦信号的跟踪效果。结果表明:Fuzzy-PID控制比常规PID控制具有更好的精度和稳定性。     

基于遗传算法的数控机床进给伺服系统模糊PID位置控制研究

文章针对电机引入的非线性、参数不确定性及对位置伺服系统快速定位和无超调的要求问题,提出了一种新的位置控制方法,即基于遗传算法的模糊PID位置控制。该方法结合遗传算法和模糊PID控制的优点,利用遗传算法优化模糊PID控制系统的模糊控制规则,通过模糊控制规则对PID参数进行实时修改。仿真结果表明,这种位置控制器具有良好的稳态精度和动态响应,与传统比例位置控制的伺服系统相比,具有良好的动态、稳态性能以及较强的鲁棒性。     

模糊自适应PID控制器在型材冷弯机送料机构的应用

针对造船工艺对型材冷弯机送料机构送料精度的要求,设计一种应用型材冷弯机的模糊自适应PID控制器。该控制器以常规PID控制为基础,根据偏差和偏差的变化率,利用模糊逻辑实现PID参数的在线调整,进一步完善了PID控制器的性能,提高了位置控制系统的精度。仿真结果表明:该控制器具有常规PID控制器高精度的特点,又具有模糊控制器响应速度快的特点,而且具有良好的动态、稳定性能以及较强的鲁棒性,能够使送料机构达到满意的控制效果。     

Robust friction compensation for submicrometer positioning and tracking for a ball-screw-driven slide system

Ball-screw-driven slide systems are largely used in industry for motion control applications. Their performance using standard proportional-integral-derivative (PID) control algorithm is unsatisfactory in submicrometer motion control because of nonlinear friction effects. In this article, controllers based on a bristle-type nonlinear contact model are developed and implemented for submicrometer motion. For submicrometer positioning, a proportional-derivative (PD) control scheme with a nonlinear friction estimate algorithm is developed, and its performance is compared with that of a PID controller. For tracking, a disturbance observer was added to reject external disturbances and to improve robustness. The experimental results indicate that the proposed controller has consistent performance in positioning with under 1.5% of steady-state error in the submicrometer range. For tracking performance, the proposed controller shows good and robust tracking with respect to parameter variation.     

永磁同步电机的模糊滑模控制

为了实现高性能永磁同步电动机伺服系统快速而精确的位置跟踪控制,在滑模控制策略中引入模糊控制算法,设计了基于模糊规则的滑模控制器;并通过理论分析和控制仿真,证实了模糊滑模控制很好地解决了抖振问题,对参数变化和负载扰动具有很好的鲁棒性,永磁同步电机可获得很好的位置跟踪效果。     

沿任意倾斜面的机器人力/位置控制方法研究

设计了沿任意倾斜面的机器人自适应阻抗控制方法,该方法解决了接触面法向方向、环境阻尼、刚度参数未知对机器人力/位置控制的影响问题。在机器人与倾斜面碰撞接触过程中采用递归最小二乘(RLS)算法估计环境的阻尼、刚度,根据接触力矩实际值与期望值的偏差实现机器人末端期望姿态的调整;在机器人末端沿倾斜面滑动阶段,设计规则自调整的模糊控制器,根据机器人末端位移、接触力误差实时调整机器人阻抗控制模型参数,以适应环境阻尼、刚度的变化。提出的控制方法具有编程实现简单且对环境参数变化鲁棒性较强的优点,实验验证了控制方法的有效性。     

液压机械手电液比例系统模糊PID控制研究

针对液压机械手的电液比例系统存在较大程度的系统参数变化和负载干扰等特点,一般控制方法难以全部满足性能要求。常规PID控制方法虽然算法简单、可靠性好、鲁棒性高,但由于参数整定繁杂,往往造成参数整定不良、性能欠佳、适用性能差。为了改善这些缺陷,将模糊控制理论与PID控制理论相结合,设计了模糊PID控制器,实现了对PID参数的在线整定。利用MATLAB/Simulink进行仿真,比较常规PID控制与模糊PID控制下电液比例系统的控制效果,发现模糊PID控制器较好地克服了系统的非线性和负载干扰的影响,提高了系统的稳定性和动态性能。