基于低通滤波器的跳跃机器人滑模控制

针对单关节跳跃机器人的轨迹跟踪、速度跟踪和振动问题,提出一种基于低通滤波器的滑模控制算法。基于Lynapunov算法设计滑模控制律,并对该算法进行了稳定性分析。利用MATLAB对单关节跳跃机器人的控制器进行了动态仿真,仿真结果表明:该算法能够快速地实现单关节跳跃机器人的位置跟踪和速度跟踪,并且相比未加入低通滤波器的单关节跳跃机器人,加入低通滤波器的单关节跳跃机器人能很好地抑制抖振,从而提高了机器人的工作品质。     

焊接机器人非奇异Terminal滑模控制系统研究

针对焊接机器人不确定性系统的特点,进行了非奇异Terminal滑模控制系统研究。建立了焊接机器人动态模型;确定了控制系统的硬件结构,并在此基础上探讨了系统非奇异Terminal滑模控制的基本原理。最后,结合实例对焊接机器人非奇异Terminal滑模控制系统进行了数值仿真。结果表明,该控制系统的自适应性强,精度高,误差可以快速收敛到0。     

积分滑模控制及抖振抑制研究用于仿人机器人头部控制

介绍了HIT三自由度仿人机器人头部的机械和电气结构,将积分滑模控制算法应用于头部追踪控制,实现了对闭环系统极点的任意配置,克服了建模不准确、外部干扰等因素的影响,使滑动模态发生在运动初始时刻,并贯穿于整个响应过程。同时提出了一种简单易行的方法切换函数比例法来抑制积分滑模控制的抖振。经与传统的PID加摩擦力补偿控制和基于计算力矩法的滑模变结构控制对比,实验证明了提出的控制方法具有较高的跟踪精度并且抖振较小、抗干扰性较强。     

机器人关节滑模变结构的位置控制

为了使机器人关节有良好的静态特性,并具有一定的抗干扰能力,提出了一种由力矩电机和谐波减速机组成的机器人关节,采用指数趋近律的滑模变结构和模糊自适应滑模控制对机器人关节进行了位置控制,通过对机器人单关节Simulink建模仿真比较,结果表明,模糊自适应滑模控制大大减轻了指数趋近律滑模控制的抖振问题,其稳态精度达到了9×10-5rad;且与PID控制相比较,其响应速度快;在受高斯扰动时,采用模糊自适应滑模控制的关节发生的角度偏差整整比PID控制小10倍。仿真结果表明,滑模控制在机器人关节控制中精度高,响应速度快,具有一定的鲁棒性能。     

基于ADAMS+MATLAB的移动焊接机器人运动仿真

基于虚拟样机技术对在狭小空间内实现焊接自动化的移动焊接机器人进行研究。采用两自由度轮式移动平台,与万向球形成三点支撑,十字滑块作为二级精确运动平台,配合旋转电弧传感器可完成对平面焊缝的精确跟踪。建立了移动焊接机器人数学模型并讨论其运动学方程。在ADAMS中建立虚拟样机并验证其正确性。针对本移动焊接机器人机构特点,采用ADAMS+MATLAB联合仿真技术对移动焊接机器人移动平台进行分析,使用PID控制对两驱动轮转速进行仿真控制,仿真得出了速度响应曲线,为物理样机实验提供了理论基础。     

焊接机器人的发展现状和机器人焊接质量控制

焊接是金属加工中的第三大产业,仅次于装配和机械加工。目前,信息、能源、材料等技术发展日新月异,推动机器人技术加速发展,工业机器人也迎来升级换代、跨越发展的机遇。焊接机器人以其独特的优势在工业生产中占有重要地位,结合其发展现状,从焊接人员、焊前准备、焊中控制和焊后处理4个方面简要概述了提高焊接质量的方法,为我国焊接机器人的技术发展和焊接质量提高提供思路。     

轮式移动焊接机器人输出反馈线性化控制

针对目前基于运动学模型的焊缝跟踪控制已经不能满足焊缝跟踪的高精度要求的问题,以一种后两轮差速驱动的5自由度轮式移动焊接机器人为对象,给出其动力学模型及其输出反馈线性化的过程,并提出一种基于此动力学的轮式移动焊接机器人路径跟踪控制方法。建立轮式移动机器人具有非完整力学系统形式的动力学模型,并推导出对应的状态反馈精确线性化模型。在此线性化模型基础上,考虑机器人动力学模型参数的不确定性,利用滑模变结构控制方法来设计动力学控制规律,选取线性切换函数和指数趋近律,设计滑模变结构控制器。并利用Lyapunov稳定性理论证明系统的稳定性且跟踪误差收敛,满足了移动机器人的轨迹跟踪要求,且具有设计方法简单、鲁棒性强的特点。通过仿真验证所提控制律的有效性和正确性。     

快速终端滑模控制在并联机器人中的应用

针对二自由度冗余驱动并联机器人,提出了并联机器人的快速终端滑模控制(FTSMC)以实现其鲁棒控制,并利用Lyapunov函数证明了该控制系统的稳定性。仿真结果表明,该控制系统跟踪效果好,系统误差小,可以满足并联机器人控制的要求。与采用普通滑模控制相比,该控制系统具有状态响应速度快,系统状态在有限时间内收敛到零的特点。仿真实验证实了该控制策略的正确性和有效性。     

基于反演的机器人滑模变结构控制研究

基于滑模变结构控制理论,针对地面机器人这类非线性强耦合系统,提出了一种反演滑模变结构控制方法.该方法将复杂的非线性系统分解成不超过系统阶数的子系统,然后为每一个子系统设计李雅普洛夫函数和中间虚拟控制量,一直回推到整个系统,直到完成整个控制律的设计.最后利用所提出的方法设计了平面二自由度机器人的控制系统并进行了仿真,仿真结果表明该控制方法的有效性.     

挖掘机器人伺服系统神经网络滑模控制

挖掘机器人伺服系统存在高度非线性、参数不确定和未建模动态等诸多不利因素,提出了一种结合径向基函数(RBF)神经网络的非线性滑模控制器,以提高控制精度和鲁棒性.首先,建立了单联伺服系统的数学模型;其次,采用RBF神经网络对系统的不利因素进行逼近,提出积分滑模面进一步减小稳态误差,同时减少对伺服系统参数的依赖,在此基础上,...     

移动机器人的准滑模控制研究

基于滑模变结构控制理论,针对移动机器人这类非完整系统,提出了一种准滑模控制方法.该方法利用李雅普洛夫函数和指数趋近律方法,设计移动机器人的控制律,结合准滑模方法,使用饱和函数代替符号函数,以降低因采用滑模变结构控制方法而产生的抖振.运用所提出的方法设计了轮式移动机器人的控制系统并进行了仿真,仿真结果验证了所提出的控制策略的有效性,并且能够有效地降低系统的抖振.     

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles.     

挖掘机器人的模型与自适应模糊滑模控制

为实现挖掘机器人的自动挖掘,在挖掘机器人的轨迹规划器给出铲斗期望运动轨迹的情况下,需要挖掘机器人的控制系统能够控制其工作装置实现对给定轨迹的准确跟踪.利用拉格朗日方法建立了挖掘机器人工作装置的三自由度动力学方程,设计了自适应模糊滑模变结构控制器.利用模糊控制动态调节切换增益,将滑模控制的切换项转化为连续的模糊系统,增强了控制系统对挖掘机器人工作装置不确定性和外界干扰的鲁棒性,削弱了滑模控制的抖振现象,并且有较强的自适应跟踪能力.利用MATLAB7.4/Simulink工具箱对所设计的控制器进行了仿真,给出了自适应模糊滑模控制的跟踪性能及误差.     

多关节移动机械臂系统的快速终端滑模控制

为了实现多关节移动机械臂系统在机械摩擦和模型误差等干扰下的精确控制,提出了快速终端滑模控制方法.首先建立了移动机械臂系统动力学和运动学模型,然后设计了运动环控制律,并将移动机械臂系统的运动指令转换为动力指令,最后针对动力环设计了快速终端滑模控制律,并通过自适应神经网络进行干扰估计,实现了对多关节移动机械臂系统的精确控制.仿真实验结果表明,提出的方法具有更好的快速性和准确性,移动平台的最大跟踪误差仅为0.8 cm,关节末端的最大跟踪误差仅为0.3 cm,干扰估计的最大误差为0.2 N·m,控制效果和精度均得到了明显的提升.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

Sliding mode control of two-wheeled welding mobile robot for tracking smooth curved welding path

In this paper, a nonlinear controller based on sliding mode control is applied to a two-wheeled Welding Mobile Robot (WMR) to track a smooth curved welding path at a constant velocity of the welding point. The mobile robot is considered in terms of dynamics model in Cartesian coordinates under the presence of external disturbance, and its parameters are exactly known. It is assumed that the disturbance satisfies the matching condition with a known boundary. To obtain the controller, the tracking errors are defined, and the two sliding surfaces are chosen to guarantee that the errors converge to zero asymptotically. Two cases are to be considered : fixed torch and controllable torch. In addition, a simple way of measuring the errors is introduced using two potentiometers. The simulation and experiment on a two-wheeled welding mobile robot are provided to show the effectiveness of the proposed controller.     

Improving tracking performance of industrial SCARA robots using a new sliding mode control algorithm

This paper addresses the implementation of a new sliding mode control algorithm for high speed and high precision tasks, which is robust against variations in the robot parameters and load. The effects of nonlinear dynamics, which are difficult to model accurately, become prominent in high speed operations. This paper attempts to treat the nonlinear dynamics of a SCARA robot as a disturbance. Based upon this approach, a new sliding mode control algorithm is proposed, in which a switching control input can be obtained easily and is determined to satisfy the existence condition for sliding mode control. A graphic simulator is used to evaluate the proposed algorithm for a SCARA robot. Simulation results show that the proposed algorithm is robust against disturbances and can reduce the magnitude of chattering, which is an unavoidable problem in sliding mode control. Experiments are carried out to validate the simulated results with an industrial SCARA robot using DSPs.     

麦克纳姆轮移动底盘的自适应滑模控制器设计

针对麦克纳姆轮移动机器人的轨迹跟踪问题,设计了一种自适应滑模控制器。首先,考虑外部干扰以及参数变化,建立了麦克纳姆轮移动机器人的运动学和动力学模型,在动力学模型的基础上设计一种自适应滑模轨迹跟踪控制器。其次,为了实现较好的运动控制,径向基神经网络被用来在线逼近动力学模型中的不确定项。同时,具有σ修正的自适应学习法则被用来估计未知的参数。再者,利用Lyapunov理论分析了该控制方法的稳定性和鲁棒性。最后,仿真结果验证了所提出控制器的有效性。