Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators

A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Impedance force control for position controlled robotic manipulators under the constraint of unknown environments

A force control strategy for position controlled robotic manipulators is presented. On line force feedback data are employed to estimate the local shape of the unknown constraint. The estimated vectors are used to generate the virtual reference trajectory for the target impedance model that is driven by the force error to produce command position. By following the command position trajectory the robotic manipulator can follow the unknown constraint surface while keeping an acceptable force error in a manner depicted by the target impedance model. Computer simulation on a 3 linked planar manipulator and experimental studies on an Adept 3, an SCARA type robotic manipulator, are conducted to verify the force tracking capability of the proposed control strategy.

Hybrid H_2/H_∞ force/position control based on neural networks

A neural network control scheme with mixed H2/H∞performance was proposed for robot force/position control under parameter uncertainties and external disturbances. The mixed H2/H∞tracking performance ensures both robust stability under a prescribed attenuation level for external disturbance and H2optimal tracking. The neural network was introduced to adaptively estimate nonlinear uncertainties, improving the system’s performance under parameter uncertainties as well as obtaining the H2/H∞tracking performance. The simulation shows that the control method performs better even when the system is under large modeling uncertainties and external disturbances.

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.

Adaptive hybrid force/position control for an industrial robot： theory and experiments

This paper proposes a feasible force/position control method for industrial robots utilized for such tasks as grinding, polishing, deburring, and so on. Specifically, an adaptive force/position control strategy is designed in this paper which regulates the contact force between a robot and a workpiece to reach any given set-point exponentially fast, and enables the robot to follow a chosen trajectory simultaneously without requiring prior knowledge of the system parameters. The stability of the closed-loop system is analyzed by Lyapunov techniques. To test the validity of the force/position control method, some simulation results are first collected for the closed-loop system. Furthermore, some experiments are implemented on a 5DOF （degree of freedom） industrial robot for the constructed adaptive force controller. Both simulation and experiment results demonstrate the superior performance of the designed adaptive force/position control strategy.

Robot Position Control Using Force Information for Cooperative Work in Remote Robot Systems with Force Feedback

This paper proposes robot position control using force information for cooperative work between two remote robot systems with force feedback in each of which a user operates a remote robot by using a haptic interface device while observing work of the robot with a video camera. We also investigate the effect of the proposed control by experiment. As cooperative work, we deal with work in which two robots carry an object together. The robot position control using force information finely adjusts the position of the robot arm to reduce the force applied to the object. Thus, the purpose of the control is to avoid large force so that the object is not broken. In our experiment, we make a comparison among the following three cases in order to clarify how to carry out the control effectively. In the first case, the two robots are operated manually by a user with his/her both hands. In the second case, one robot is operated manually by a user, and the other robot is moved automatically under the proposed control. In the last case, the object is carried directly by a human instead of the robot which is operated by the user in the second case. As a result, experimental results demonstrate that the control can help each system operated manually by the user to carry the object smoothly.

A Review of Robotic Force/Position Control

This paper reviews robotic position and force control techniques. The existing fundamental force control algorithms are compared and discussed, including explicit/implicit control, stiffness control, impedance/admit- tance control, and hybrid position/force control. This work is intended to give a basic guidance for understanding and utilization of the fundamental robotic control algorithm.

Robust scheme of global parallel force/position regulators for robot manipulators under environment uncertainty

A simple robust scheme of parallel force/position control is proposed in this paper to deal with two problems for non-planar constraint surface and nonlinear mechanical feature of environment： i） uncertainties in environment that are usually not available or difficult to be determined in most practical situations; ii） stability problem or/and integrator windup due to the integration of force error in the force dominance rule in parallel force/position control. It shows that this robust scheme is a good alternative for anti-windup. In the presence of environment uncertainties, global asymptotic stability of the resulting closed-loop system is guaranteed; it environment with complex characteristics. Finally, numerical robot manipulator. also shows robustness of the proposed controller to uncertain simulation verifies results via contact task of a two rigid-links

Robust decentralized adaptive output feedback fuzzy controller design and application to AHS

A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.

Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

双悬臂截割机器人相对动力学建模与力位混合控制研究

双悬臂截割机器人可解决传统单臂掘进机在截割大尺寸断面时效率低下的难题,但其与煤岩的动态交互影响控制性能。现有研究以双臂接触同一对象形成运动闭链为前提,无法满足双悬臂截割机器人双臂运动及末端截割头输出力的控制要求。针对该问题,设计了一种基于机器人相对动力学模型的力位混合控制系统。建立双悬臂截割机器人运动学和动力学模型,基于机器人的相对雅可比矩阵及虚位移与虚功原理推导出机器人的相对动力学模型,通过单一变量同时描述机器人双臂的运动状态,将机器人双臂独立的动力学模型整合为一个整体。基于机器人的相对动力学模型,设计了机器人双臂力位混合控制系统,通过李雅普诺夫函数验证了系统的稳定性和可行性。仿真结果表明:双悬臂截割工艺较单悬臂截割拥有更大的工作空间,具有一次性实现大断面截割的能力;双悬臂截割机器人力位混合控制系统能够完成对期望相对位置和期望相对力的同步跟踪,对截割头期望位置跟踪的绝对误差在0.3132 m以内,均方根误差为0.1447 m。

Position/Force Hybrid Control System for High Precision Aligning of Small Gripper to Ring Object

A position/force hybrid control system based on impedance control scheme is designed to align a small gripper to a special ring object. The vision information provided by microscope vision system is used as the feedback to indicate the position relationship between the gripper and the ring object. Multiple image features of the gripper and the ring object are extracted to estimate the relative positions between them. The end-effector of the gripper is tracked using the extracted features to keep the gripper moving in the field of view. The force information from the force sensor serves as the feedback to ensure that the contact force between the gripper and the ring object is limited in a small safe range. Experimental results verify the effectiveness of the proposed control strategy.

高压阀口液动力补偿控制策略仿真分析

直动式比例伺服阀是一种新型的单级伺服阀,采用比例电磁铁或线性力马达直接驱动滑阀运动,具有成本低、频响高、抗污染能力强等优点,广泛应用于注塑机进给控制、轧机板厚控制系统等高速高精度液压控制系统中。传统的直动式比例伺服阀采用PID控制策略实现阀芯的精确位置控制,在高压大流量工况下(供油压力达到20 MPa、流量大于100 L/min),阀芯受到液动力扰动变得更加剧烈,易出现响应速度慢、阀芯抖动的现象,影响了比例伺服阀的控制精度。为了解决大液动力扰动的问题,提出了一种基于指数收敛干扰观测器的滑模控制器。通过建立阀芯动力学模型来设计滑模控制器,保证阀芯位置的高动态跟踪性能;使用基于指数收敛的干扰观测器,估计阀芯动力学模型中液动力的不确定性扰动,解决高压大流量工况下的阀芯液动力扰动补偿问题。搭建了比例伺服阀系统的联合仿真模型进行仿真验证,结果表明,提出的控制器可以解决高压大流量工况下阀芯液动力扰动对阀芯位置控制的干扰问题。

铆接机器人位置和压铆力自适应模糊滑模阻抗控制

针对机器人铆接小尺寸、低刚度铆钉过程中对准精度要求高、作业行程小和冲击力大等问题,提出了一种结合自适应模糊滑模控制和模糊阻抗控制的机器人铆接控制方法。为此,将机器人铆接控制过程分为接近对准与压铆两个阶段。其中,为了实现快速接近铆钉顶部以及铆接头与铆钉轴线的精确对准,设计了以双曲正切函数为切换函数的模糊自适应滑模控制器,使得切换过程更加光滑、滑模增益自适应调节,从而降低了系统的抖振,实现了运动的快速性和准确性;针对压铆阶段作业行程小、冲击力大的特点,设计了以接触力误差和力增量为输入的阻尼调整模糊控制器,减少了阻尼参数在阻抗控制过程中产生的振荡,避免了过度力加载导致的铆钉损坏或铆接失败。仿真及试验结果表明,所给出的控制方法位置精度在0.3 mm以内,力接触具有更好的稳定性、实时性和快速性,能够满足铆接工艺规范要求,对于铆接机器人的高精度作业具有借鉴意义。

单绳缠绕式矿井提升机制动瞬态冲击抑制策略

在矿井提升机的制动控制中,制动瞬态冲击是影响矿井提升机安全可靠运行的关键问题。由于受到技术和经济成本的制约,目前包含贴闸/压紧的制动过程全程采用力闭环控制,这不可避免地导致闸瓦与闸盘刚性接触时的制动力瞬态冲击问题。针对矿井提升机制动瞬态冲击问题,文中提出了一种基于滞回切换原理的混合贴闸/压紧制动控制策略。首先,分别利用非奇异快速终端滑模控制和反步控制设计了贴闸和压紧控制器;其次,为达到快速贴闸的目的,设计了一种基于离散积分器的在线贴闸轨迹再规划方法,有效地减小了制动器贴闸时间;然后,为实现由贴闸控制到压紧控制的安全切换,利用滞回切换原理,制定了混合贴闸/压紧控制稳态切换策略,大大减小了制动力瞬态冲击;最后,为验证提出方法的有效性,选择传统全程力闭环控制策略C1与混合贴闸/压紧直接切换策略C2作为对比方法,在单绳缠绕式提升试验台进行了对比实验,从贴闸时间、制动力最大跟踪误差和提升钢丝绳最大张力3个方面对实验结果进行了分析。实验结果表明:相较于C1控制策略,提出制动控制策略的贴闸时间缩短了64.5%,钢丝绳张力峰值减小了41 N;相较于C2控制策略,提出制动控制策略的制动力冲击减小了90.3%,钢丝绳张力峰值减小了88 N。上述结果表明本文提出的方法能有效改善制动瞬态冲击,减小制动空动时间,提高制动系统安全性,同时本研究也为一类需要混合力/位置控制的电液伺服系统提供了一种有效的解决方法。

基于AMESim-Matlab联合仿真的拖拉机耕深控制研究

在拖拉机电控液压耕深控制系统的研究中提出力位综合-滑转率的联合控制方法及控制策略,加入滑转率监测控制,在最优滑转率区间允许范围内调节耕深。搭建电控液压悬挂的液压物理模型,并建立仿真模型,设计滑转率模糊控制器、力位综合模糊PID控制器,试验研究基于滑转率逻辑门限的多参数控制效果。试验结果表明在超出滑转率逻辑门限值时系统有较好的响应效果,对滑转率的变化有较优的跟随效果,为拖拉机耕深控制系统多参数控制提供理论基础。

基于力控技术的航空整体加强框自适应定位方法研究

为了减弱制造差异对航空整体加强框装配定位质量的影响,解决强迫定位造成的定位过程管控性差和定位结果复现度低的难题,基于力控技术提出一种航空整体加强框自适应定位方法,按传统强迫方式完成装配定位后,在设计允许范围内调整若干坐标定位孔位置,至孔位处力载值满足自适应定位要求。针对航空整体加强框装配定位工艺对形位精度、装配应力水平的要求,量化装配定位质量评价标准,基于正交试验分析定位孔处力载绝对平均值和定位检测点处应力绝对平均值的变化规律,进行装配现场易于获取的力载值取代应力值的可行性研究,通过修正装配定位质量评价标准量化公式得到坐标定位孔处力载调整目标,指导航空整体加强框装配定位。

面向复杂曲面力控抛光的变阻抗控制研究

针对复杂曲面的力控抛光任务中同时控制刀具进给速度与接触力困难的问题,分析了在刀具期望进给速度与接触力方向时变场景下基于经典力位混合方法的柔顺控制算法难以控制的原因,提出了一种新的基于时变力位混合框架及自适应导纳控制的柔顺控制算法。使用工件轮廓曲率实时修正力位混合框架,减小进给速度与接触力控制之间的耦合影响,并使用接触力误差与力位混合框架修正速度来自适应调整导纳控制的阻尼参数。仿真验证了所提算法可解决传统算法在时变力位跟踪时的接触力不收敛问题,且所提自适应策略可进一步降低超过80%的接触力跟踪误差。

基于自抗扰控制的机械臂末端力/位置控制

针对机械臂末端力/位置控制问题,提出一种基于自抗扰控制(ADRC)的间接力/位置混合阻抗控制方案,将间接力/位置混合控制与阻抗控制相结合,在机械臂未与环境接触时采用位置控制,在与环境接触后切换为间接力控制,并体现出阻抗特性。该方案将混合阻抗控制与ADRC相结合,根据机械臂与环境接触时的阻抗模型建立ADRC控制器,并将阻抗参数视为系统总扰动的一部分,利用扩张状态观测器进行估计补偿,实现在无需计算阻抗参数的情况下使间接力/位置混合阻抗控制器在面对扰动时有较好的稳定性和鲁棒性。完成二自由度机械臂模型的仿真,并与传统阻抗控制器进行了比较,结果验证了所提出的基于ADRC的间接力/位置混合阻抗控制方案的有效性。