Effects of Joint Controller on Analytical Modal Analysis of Rotational Flexible Manipulator

Modal analysis is a fundamental and important task for modeling and control of the flexible manipulator. However, almost all of the traditional modal analysis methods view the flexible manipulator as a pure mechanical structure and neglect feedback action of joint controller. In order to study the effects of joint controller on the modal analysis of rotational flexible manipulator, a closed-loop analytical modal analysis method is proposed. Firstly, two exact boundary constraints, namely servo feedback constraint and bending moment constraint, are derived to solve the vibration partial differential equation. It is found that the stiffness and damping gains of joint controller are both included in the boundary conditions, which lead to an unconventional secular term. Secondly, analytical algorithm based on Ritz approach is developed by using Laplace transform and complex modal approach to obtain the natural frequencies and mode shapes. And then, the numerical simulations are performed and the computational results show that joint controller has pronounced influence on the modal parameters： joint controller stiffness reduces the natural frequency, while joint controller damping makes the shape phase non-zero. Furthermore, the validity of the presented conclusion is confirmed through experimental studies. These findings are expected to improve the performance of dynamics simulation systems and model-based controllers.

Dynamic analysis of multi-link spatial flexible manipulator arms with dynamic stiffening effects

The dynamics for multi-link spatial flexible manipulator arms is investigated. The system considered here is an N-flexible-link manipulator driven by N DC-motors through N revolute flexiblejoints. The flexibility of each flexible joint is modeled as a linearly elastic torsional spring, and the mass of the joint is also considered. For the flexibility of the link, all of the stretching deformation, bending deformation and the torsional deformation are included. The complete governing equations of motion of the system are derived via the Lagrange equations. The nonlinear description of the deformation field of the flexible link is adopted in the dynamic modeling, and thus the dynamic stiffening effects are captured. Based on this model, a general-purpose software package for dynamic simulation of multi-link spatial flexible manipulator arms is developed. Several illustrative examples are given to validate the algorithm presented in this paper and to indicate that not only dynamic stiffening effects but also the flexibility of the structure has significant influence on the dynamic performance of the manipulator.

Method for optimizing manipulator's geometrical parameters and selecting reducers

A geometrical parameters optimization and reducers selection method was proposed for robotic manipulators design. The Lagrangian approach was employed in deriving the dynamic model of a two-DOF manipulator. The flexibility of links and joints was taken into account in the mechanical structure dimensions optimization and reducers selection, in which Timoshenko model was used to discretize the hollow links. Two criteria, i.e. maximization of fundamental frequency and minimization of self-mass/load ratio, were utilized to optimize the manipulators. The NSGA-II (fast elitist nondominated sorting genetic algorithms) was employed to solve the multi-objective optimization problem. How the joints flexibility affects the manipulators design was analyzed and shown in the numerical analysis example. The results indicate that simultaneous consideration of the joints and the links flexibility is very necessary for manipulators optimal design. Finally, several optimal combinations were provided. The effectiveness of the optimization method was proved by comparing with ADAMS simulation results. The self-mass/load ratio error of the two methods is within 10%. The maximum error of the natural frequency by the two methods is 23.74%. The method proposed in this work provides a fast and effective pathway for manipulator design and reducers selection.

Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

Robotic manipulators are widely used in applications that require fast and precise motion.Such devices,however,are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part.To address these issues,the Linear Matrix Inequalities(LMIs)and Parallel Distributed Compensation(PDC)approaches are implemented in the Takagy–Sugeno Fuzzy Model(T-SFM).We propose the following methodology;initially,the state space equations of the nonlinear manipulator model are derived.Next,a Takagy–Sugeno Fuzzy Model(T-SFM)technique is used for linearizing the state space equations of the nonlinear manipulator.The T-SFM controller is developed using the Parallel Distributed Compensation(PDC)method.The prime concept of the designed controller is to compensate for all the fuzzy rules.Furthermore,the Linear Matrix Inequalities(LMIs)are applied to generate adequate cases to ensure stability and control.Convex programming methods are applied to solve the developed LMIs problems.Simulations developed for the proposed model show that the proposed controller stabilized the system with zero tracking error in less than 1.5 s.

Sliding Mode and PI Controllers for Uncertain Flexible Joint Manipulator

This paper is dealing with the problem of tracking control for uncertain flexible joint manipulator robots driven by brushless direct current motor(BDCM). Flexibility of joint in the manipulator constitutes one of the most important sources of uncertainties. In order to achieve high performance, all parts of the manipulator including actuator have been modeled. To cancel the tracking error, a hysteresis current controller and speed controllers have been developed. To evaluate the effectiveness of speed controllers, a comparative study between proportional integral(PI) and sliding mode controllers has been performed. Finally, simulation results carried out in the Matlab simulink environment demonstrate the high precision of sliding mode controller compared with PI controller in the presence of uncertainties of joint flexibility.

Spiking-free HGO-based DSC for flexible joint manipulator

The tracking control problem for Flexible Joint Manipulator Control System(FJMCS)with unmeasurable states is addressed in this paper.Firstly,a High-Gain Observer(HGO)is constructed to estimate the unmeasurable states and the uncertainties.Then,a Dynamic Surface Control(DSC)scheme is developed by using the estimation of HGO.The newly proposed controller has two advantages over the existing methods:(A)a novel Spike Suppression Function(SSF)is developed to avoid the estimation spike problem in the existing HGO-based controllers.(B)Unlike the existing observer-based partial feedback control scheme that can only estimate the unmeasurable states,the proposed HGO can estimate both the unmeasurable states and uncertainties.The closed-loop system stability is proved by the Lyapunov theory.Simulation results demonstrate the effectiveness of the proposed controller.

柔性关节空间机械臂传感容错无模型自适应控制

针对传感信号畸变、丢失等故障状态严重影响空间机械臂控制系统性能的问题,提出基于空间机械臂运动传感器故障观测的无模型自适应容错控制方法。采用动态线性化和递推参数估计思想设计传感故障监测器,实现对传感畸变及数据丢失等故障的判定,并进行运动状态预测估计;建立包含跟踪误差变化率项的无模型自适应控制准则函数,有效惩罚由传感故障引起的参数估计突变问题;设计面向柔性关节空间机械臂的新型传感容错无模型自适应控制(SFT-MFAC)算法。仿真结果表明,在不同传感故障情况下,所提控制策略均能快速准确识别传感故障信息,避免系统瞬时发散,有效延长系统响应时间,增加控制系统的鲁棒性。

水液压扭转关节的结构优化设计与试验

针对压力流体驱动的柔性机械手操作空间有限、支撑刚度不足等问题,提出一种由水液压驱动的新型扭转关节。通过有限元分析方法,对不同结构参数以及不同系统压力下关节的扭转变形特性进行了分析。基于Kriging代理模型混合优化算法获得扭转关节最大扭转角度对应的最佳结构参数组合,并对水液压扭转关节进行了试验研究。结果表明:试验与仿真的关节扭转角随系统压力变化的趋势基本一致,当系统压力为0.6 MPa时,扭转关节达到最大扭转角度,约为40°,且试验与仿真结果误差低于2%。为扭转关节设计和驱动方式提供了新思路、新方法。

具有柔性驱动关节的串并混联仿生机械臂

现有协作机器人多采用串联刚性结构,与人的共融性较差,限制了机器人的应用场景.为解决协作机器人在柔顺性和环境适应性上的不足,首先,基于人体手臂肌肉柔性并联驱动机理,设计一种6自由度串并混联机械臂SoftArm-6,由臂部3个串联自由度和腕部3个并联自由度组成,采用电机串联弹性驱动器(Series Elastic Actuator,SEA)构成柔性驱动关节,通过建立机械臂的运动学模型,基于机构等效原理实现串并混联机械臂的位姿解耦.其次,基于Kinect人体运动捕捉的在线轨迹示教方法,针对驱动关节中SEA柔性环节带来的位置精度降低、易抖动等问题,设计基于虚位移原理的前馈重力补偿算法.最后,针对SoftArm-6样机设计轨迹跟随、示教抓取等实验.研究结果表明:SoftArm-6在轨迹跟随任务中的偏差小于1.5%,抓取成功率达98%,显著提升了操作精度和环境适应性.该设计为协作机器人在复杂、不确定环境中的应用提供了新的技术支持.

模糊整定PI参数的双柔性机械臂振动抑制

机械臂伺服驱动系统中柔性因素的存在易导致机械臂输出转速波动,甚至引发系统谐振.为抑制系统转速波动,使机械臂传动系统性能稳定,使用模糊理论整定PI控制器参数的控制策略.根据假设模态法和拉格朗日动力学方程建立了考虑LuGre摩擦模型的双柔性机械臂传动系统动力学方程,并分析了动力学方程中耦合非线性项对系统传动特性的影响.使用极点配置策略确定PI控制器参数的取值范围,后根据模糊规则实时调整控制器参数,以减小伺服系统输出转速的波动,进而抑制系统谐振.最后,借助数值仿真分析和机械臂控制实验,与传统PI控制策略对比,发现本文所述控制策略可使电机端转角跟踪误差绝对值的平均值降低43.066%,柔性负载转角误差的标准差降低46.506%,更加验证了所提模糊规则整定PI控制器参数抑振方法的有效性.

基于状态约束的柔性关节机械臂指令滤波控制

针对单连杆柔性关节机械臂系统,研究了全状态约束条件下机械臂末端位置的跟踪控制问题。利用障碍李雅普诺夫函数约束柔性关节机械臂的关节角位置和电机转角位置等状态变量的幅值,保证所有状态变量不会超出给定的限制区域。在此基础上,通过引入带有误差补偿的指令滤波控制技术克服了传统反步法存在的计算爆炸问题,设计了基于状态约束的指令滤波反步控制器。最后,基于李雅普诺夫稳定性理论证明了柔性关节机械臂系统的稳定性,并通过仿真实验验证了所设计的控制器能够有效保证系统的状态约束性能和位置跟踪精度。

基于仿生优化神经网络的6DOF工业机械手标定

针对六自由度工业机械手标定中的定位精度问题,提出一种基于仿生优化神经网络的机械手标定方法。研究六自由度工业机械手的运动学模型,并给出其D-H参数。通过将关节挠度模型和传统的运动学模型标定技术相结合,来同步识别机械手的运动学参数和柔度参数,以提高定位精度。然后,构造人工神经网络对未建模误差进行进一步补偿,如摩擦、机械传动误差和热膨胀。此外,采用入侵杂草优化算法对神经网络的权值和偏置进行优化。最后,采用六自由度机械手HX300对所提方法进行了实际测试,验证其可行性。研究结果表明:标定后机械手的定位精度得到了显著提高,平均误差、最大误差和标准差分别为0.345、0.6374、0.1624 mm,均小于其他标定方法;与GA-BP神经网络标定方法相比,所提方法具有更好的收敛能力,平均误差降低了15.92%,适用于高精度的各种工业应用。

具有执行器故障的柔性机械臂预定精度控制

探讨了具有动态不确定性的柔性机械臂故障补偿问题。由于系统的机械设备出现老化、磨损或维修过程出现操作不当,会导致执行器部分失效或卡死,但在执行器故障期间与故障相关的参数难以测量。若系统发生执行器故障,可能会对系统的稳定性造成影响,甚至会使系统出现不稳定的情况。使用自适应控制方法,处理存在未知模式的执行器故障以及参数故障的情况,保证系统快速补偿达到稳态状态。并且,通过使用模糊逻辑系统处理未知的非线性函数,并结合一类光滑函数作为控制器设计,保证系统跟踪误差收敛到指定的性能区间。仿真实验中,以单连杆柔性机械臂控制的故障补偿为例,证明了本文所提控制方案的有效性。

单连杆柔性关节机械臂的高阶滑模控制器设计

针对单连杆柔性关节机械臂系统,提出了一种基于高阶滑模算法的有限时间镇定控制方法。所提出的方法涉及两个关键方面。首先,通过引入加幂积分器,设计了一个新的李雅普诺夫函数,使得输出信号在有限时间内收敛。其次,利用符号函数抑制了系统不确定性造成的抖振现象。基于有限时间李雅普诺夫稳定性理论,证明了该算法能够保证滑动变量在有限时间内收敛到原点。最后,单连杆柔性关节机械臂的仿真结果验证了高阶滑模控制算法的有效性。

基于模糊协同交互型观测器的柔性关节机械臂信息物理融合系统的安全控制

本文研究了柔性关节机械臂信息物理融合系统(Cyber-physical systems,CPS)在传感器测量和执行器输入受到网络攻击时的安全控制问题.首先,用T-S模糊模型描述柔性关节机械臂CPS,描述后的模型可能存在不可测量或可测量但受传感器攻击影响的前件变量(Premise variables,PVs),这些PVs直接用于构建模糊控制器会影响控制器的控制效果.因此,提出一类模糊协同交互观测器来构造新的、可靠的、可利用的PVs.同时,该观测器能够与包含攻击估计误差(Attack estimation error,AEE)信息的辅助系统进行协同交互.与已有结果相比,所提出的观测器通过协同交互结构,充分利用了AEE信息,提高了攻击信号的重构精度.在此基础上,提出了一种具有攻击补偿结构的安全控制方案,从而消除了传感器和执行器攻击对柔性关节机械臂CPS性能的影响.仿真结果验证了所提出的安全控制方案的有效性.

基于反演法的矿用机械臂关节位置控制方法

针对矿用机械臂关节内部的柔性元件可导致机械臂末端位置无法实现精准控制的问题,对机械臂柔性关节的位置控制方法进行研究,基于拉格朗日动力学模型构建方法,建立融入机械臂关节柔性特性的关节动力学模型,并且与反演法原理进行结合,创新性地提出基于反演法的矿用机械臂柔性关节位置控制方法(IM-PCM),使机械臂关节柔性造成的末端位置控制精确性不足问题得到改善。通过MATLAB软件中的SIMULINK平台对IM-PCM的控制效果进行仿真分析,结果表明IM-PCM能够使矿用机械臂末端位置得到精确控制。

Identification and Control of Flexible Joint Robot Using Multi-Time-Scale Neural Network

In this paper,a new identification and control scheme for the flexible joint robotic manipulator is proposed.Firstly,by defining some new state variables,the commonly used dynamic equations of the flexible joint robotic manipulators are transformed into the standard form of a singularly perturbed model.Subsequently,an optimal bounded ellipsoid algorithm based identification scheme using multi-time-scale neural network is proposed to identify the unknown system dynamic equations.Lastly,by using the singular perturbation theory,an indirect adaptive controller based on the identified model is proposed to control the system such that the joint angles can track the given reference signals.The closed-loop stability of the whole system is proved,and the effectiveness of the proposed schemes is verified by simulations.

综合关节和杆件柔性的机械臂刚柔耦合建模与仿真

基于Lagrangian方程和转子非线性扭簧模型,建立柔性机械臂刚柔耦合动力学模型;通过假设模态法将物理坐标转换为模态坐标;利用ADAMS建立了虚拟样机,用于求解仅考虑杆件柔性时的运动;在Matlab中编写了Runge-Kutta算法,用于求解综合关节和杆件柔性时的运动。针对重力和驱动力作用下的垂直面摆动,给出了不同末端负载影响下的柔性关节转角和末端变形曲线;分析了关节柔性与杆件柔性之间的耦合关系。结果表明关节柔性不可忽略,关节和杆件柔性耦合作用下的末端振动小于两者的叠加,振型由关节和杆件的柔性确定,但幅值主要受驱动力影响。

计及关节及杆柔性的空间机械臂抓取控制

针对考虑关节及杆柔性的空间机械臂动力学与抓取控制问题,以三连杆柔性机械臂为研究对象,考虑臂杆的横向弯曲变形、纵向拉伸变形及由于横向变形引起的轴向收缩的二阶耦合量等,并通过引用转子扭簧模型来考虑柔性关节的影响,应用Lagrange方程和假设模态法建立动力学模型。引入"动态抓取域"来描述机械臂的抓取过程,采用关节主动阻尼控制来抑制抓取过程中的碰撞激振力,分析了匀速抓取和加速抓取两种策略的机械臂柔性关节的变形特性。仿真结果表明:关节柔性减小了整体碰撞力,在碰撞过程中起到一定的缓冲作用;加速抓取控制下比匀速抓取控制下的关节变形小,前者整体优于后者。

基于加速度反馈的柔性关节机械臂接触力控制

针对柔性关节机械臂从自由空间运动控制过渡到约束空间力控制的过程中,存在冲击、震荡甚至不稳定等问题,利用加速度传感器反馈控制,为柔性关节机械臂的接触力控制在较宽的带宽内提供阻尼,克服了利用单纯速度反馈控制带宽窄的局限。对柔性关节机械臂的接触力控制进行建模和基于加速度反馈的控制策略分析,并在柔性关节机械臂上进行了接触力控制的试验研究。结果表明,这种方法有效。