绳驱柔性机械臂建模与控制方法研究现状

绳驱柔性机械臂具有高形变、质量小、能耗低等优点,伴随机器人应用的发展,针对绳驱软柔性机械臂的精准建模与有效控制成为国内外学者的重点研究方向。本文综述了绳驱柔性机械臂建模与控制方法,从建模方法上分析其运动学、动力学及静力学建模,并分别从基于模型与无模型两方面对控制方法进行归纳总结。其中,基于模型的控制方法分为运动学与动力学建模两类,而无模型控制方法包括模糊控制、神经网络控制、自适应控制与滑模控制等。最后,对绳驱柔性机械臂建模与运动控制未来的研究方向进行展望。     

柔性机械臂用压电驱动器实现精密定位控制的研究——解析模型、作业空间和可操作性分析

本文提出了利用柔性机械臂的柔性并通过压电驱动器实施精密定位，实现微位移和微力操作的思想．为此针对二连杆柔性机械臂建立了其微位移、微力操作的解析模型，并理论和仿真分析其可达作业空间能力及其可操作性．通过应用例子仿真研究表明方法的有效性，拓宽了压电驱动器应用于柔性机械臂振动控制的思想     

柔性机械臂用压电驱动器实现精密定位控制的研究——解析模型、作业空间和可操作性分析

本文提出了利用柔性机械臂的柔性并通过压电驱动器实施精密定位，实现微位移和微力操作的思想．为此针对二连杆柔性机械臂建立了其微位移、微力操作的解析模型，并理论和仿真分析其可达作业空间能力及其可操作性．通过应用例子仿真研究表明方法的有效性，拓宽了压电驱动器应用于柔性机械臂振动控制的思想     

柔性机械臂末端位置的变结构模型参考自适应控制

本文用变结构方法设计柔性机械臂的模型参考自适应控制律．首先用最优状态反馈方法构造了参考模型，然后定义了末端位置误差，构造了滑模曲线，接着用变结构方法推导了自适应控制律，最后针对一具体柔性臂作了仿真研究，验证了理论的正确性并给出了一些有意义的结论．     

柔性机械臂动力学建模研究进展

刚性机械臂由于其较高的工作精度和重复性、较强的承载能力,已广泛应用于危险或相对单一、重复性高工作场景.但刚性机械臂的结构及运作方式不够灵活,无法适用于不定型、非标准、狭窄空间等生产场景.最近几年,柔性机械臂因其结构柔性、作业空间大、人机交互安全等优点而受到广泛关注,有希望应用于医疗、服务和智能制造等领域.但柔性机械臂结构柔软,运动比较自由,在作业过程中柔性效应不可忽略,这对其高精度控制提出了重大挑战.柔性机械臂控制的核心科学问题之一是建立包含结构柔性特征和动态特性的高精度动力学模型.为此,本文对柔性机械臂运动学建模和动力学建模研究进行了综述.作为动力学建模的基础,本文首先综述了柔性机械臂的运动学建模方法,主要介绍了曲率法、伪刚体运动学(PRB)方法、基于Cosserat杆的运动学建模方法、结构几何分析方法、Denavit Hartenberg(D H)法及坐标法、数据驱动和机器学习方法等.随后,本文详细综述了柔性机械臂的动力学建模方法,主要包括集中参数系统法、假设模态法、有限元法.最后,本文简述了目前柔性机械臂动力学研究的主要内容,并对未来研究做出展望.     

柔性机械臂运动轨迹的鲁棒自适应控制

本文针对多连杆柔性机械臂的运动轨迹问题，讨论了动力学建模，控制系统结构设计以及鲁棒自适应控制法，运用假设模记方法得到了柔性机械臂动力学所似方程，通过对柔性机械臂动力学特性分析，建立了等价动力学模型，依此提出了一种鲁棒自适应控制算法，并给出仿真研究结果。     

计及环境特征的刚一柔机械臂动力学建模方法与理论研究

基于Kane方程推导建立了在惯性参考坐标系中的刚一柔机械臂的非线性动力学模型，并利用假设模态的方法对方程进行离散．在对刚一柔机械臂进行主动柔顺控制时，柔性机械臂要受到未确知外部环境的约束．本文建立了计及环境特征的一般柔性多体系统动力学模型以及计及环境特征的刚一柔机械臂动力学模型．     

压电柔性机械臂的主动振动控制研究

针对柔性机械臂的振动问题,采用压电智能结构作为敏感器和驱动器进行主动控制.首先建立柔性机械臂的实验装置,其次对设计的柔性机械臂系统进行辨识研究,得到系统的前二阶模态频率,再次采用PD控制和PPF控制算法对柔性机械臂进行主动振动控制.实验结果表明,采用压电智能结构可以抑制柔性机械臂的振动,效果明显.     

机械臂自适应精确时间滑模控制

考虑机械臂中存在的未建模部分、摩擦力、外加干扰,提出一种自适应精确时间滑模控制方法,实现机械臂各关节角的轨迹跟踪.首先对机械臂进行建模,将未建模部分、摩擦力、外加扰动看作集中扰动;其次,设计一种精确时间收敛滑模面,克服传统终端滑模面收敛时间高估的问题,基于此设计全局精确时间收敛滑模控制方法,使得机械臂系统能够在设定时间实现稳定,并在误差收敛后仍具有较强的鲁棒性;接着,设计低通滤波器削减抖振,通过自适应方法估计扰动上界,避免增益的高估;最后,通过仿真实验验证所提出的控制方法能够严格控制机械臂系统的稳定时间,并降低稳态误差,实现机械臂系统的高精度轨迹跟踪控制.     

柔性机械臂的双时间尺度组合控制

本文研究柔性机械臂的轨迹跟踪和振动抑制问题. 首先, 利用Lagrange法和假设模态法建立柔性机械臂的动态模型, 进而利用奇异摄动理论得到柔性机械臂的双时间尺度模型. 然后, 基于慢时间尺度模型利用滑模控制理论设计轨迹跟踪控制器; 借助于快时间尺度模型利用自适应动态规划设计参数不精确已知情况下的最优振动抑制控制器; 将二者相结合, 构造双时间尺度组合控制器, 利用奇异摄动理论证明闭环系统稳定. 最后, 在Matlab/Simulink环境下进行实验, 与现有方法相比, 本文设计的控制器对柔性振动具有更好的振动抑制效果, 跟踪精度更高.     

A review on two-link flexible manipulators

This paper presents a survey in the field of two-link flexible manipulators (TLFMs). Two-link flexible manipulators are more used in comparison with other types of flexible manipulators. Therefore, this paper discusses various aspects of the reported works of TLFMs available in the literature. The papers based on TLFMs are classified into modeling methods, dynamical analyses, complexities involved and control schemes used. The modeling methods discuss the various types of modeling used for a TLFM. A brief note on the complexities involved in the flexible manipulators are presented. The main categories of the control problems addressed by the available papers are also discussed. The classification of the control techniques is made according to the nature of controllers. It is also mentioned in the paper as to whether the reported work deals with only simulation based results or are validated with the experimental work.     

柔性机器人的动力学建模及其控制*

本文首先综述了近年来在柔性机器人动力学建模方面所取得的进展，着重介绍了目前较常见的几种建模方法和模型，同时对柔性机器人的控制问题进行了评述，指出了今后研究的方向。     

Feedback control of a flexible cylindrical manipulator

Flexible robotic manipulators have been the subject of numerous studies in the past few years. Past studies, however, have concentrated on flexible manipulators with only revolute joints. This paper considers the case of a structurally flexible manipulator with prismatic and revolute joints; specifically, an algorithm for controlling a structurally flexible three-degree-of-freedom cylindrical manipulator is presented. The control algorithm involves two steps. Using nonlinear feedback, the equations of motion are first decoupled into three subsystems representing the three rigid degrees of freedom together with their associated ‘flexible equations’, if any. Then, using linear optimal control theory, controllers are designed for the three subsystems independently. Computer simulated results for an example system are presented.     

一种双连杆柔性臂动力学模型的研究

针对末端位置受约束的双连杆柔性机械臂,通过哈密顿原理得到系统的分布参数模型,推导了描述关节角,柔性杆振动和接触力之间关系的动力学模型.根据3个假设条件推导柔性臂简化的集中参数动力学模型及准静态方程,利用了计算力矩法设计的控制器对模型进行控制,通过Matlab进行仿真,利用Matlab的符号运算功能,编制M文件实现数学模型自动推导,整个建模和运算过程简单、直观和高效,并绘制了参数轨迹图像,验证了模型的有效性,已应用到小波神经网络控制算法研究中.     

平面双连杆受限柔性机器人臂的动力学建模*

对一类平面双连杆受限柔性机器人臂的动力学建模问题进行研究，利用Ｄ’Ａｌｅｍｂｅｒｔ－Ｌａｇｒａｎｇｅ原理得到了一组描述该机器人系统运动性态的动力学方程。与已有的动力学模型相比，本文所建立的运动方程和振动方程具有模型准确、结构简单等特点，且具有与传统无约束刚性机器人类似的模型形式，因而有可能直接或间接利用现有的关于刚性机器人运动控制等方面的成果来研究复杂的受限柔性机器人的控制问题。     

Modified PID Control of a Single-Link Flexible Robot

The use of flexible links in robots has become very common in different engineering fields. The issue of position control for flexible link manipulators has gained a lot of attention. Using the vibration signal originating from the motion of the flexible-link robot is one of the important methods used in controlling the tip position of the single-link arms. Compared with the common methods for controlling the base of the flexible arm, vibration feedback can improve the use of the flexible-link robot systems. In this paper a modified PID control (MPID) is proposed which depends only on vibration feedback to improve the response of the flexible arm without the massive need for measurements. The arm moves horizontally by a DC motor on its base while a tip payload is attached to the other end. A simulation for the system with both PD controller and the proposed MPID controller is performed. An experimental validation for the control of the single-link flexible arm is shown. The robustness of the proposed controller is examined by changing the loading condition at the tip of the flexible arm. The response results for the single-link flexible arm are presented with both the PI and MPID controller used. A study of the stability of the proposed MPID is carried out.     

Observer-Based Optimal Control of Flexible Stewart Parallel Robots

The design and simulation of two optimal control schemes for a parallel flexible link manipulator of the Stewart type is presented. The first control scheme combines a nonlinear rigid model of the flexible manipulator with a linear rigid observer, whereas the second scheme uses a nonlinear flexible manipulator model with a linear flexible observer. The majority of the results available in the literature do not address the optimal control problem through the use of observers, as it is done in this paper, for the control of parallel robots. The simulation results have shown in both cases that indeed optimal state-obscrver-based control is a good candidate for controlling parallel-link manipulators in practice. As expected, the second scheme (flexible model plus flexible observer) gives better results than the first one, achieving faster trajectory tracking. The effects of white noises, applied forces, and zero gravity environment were taken under consideration.     

Optimal Trajectory Planning for Flexible Link Manipulators with Large Deflection Using a New Displacements Approach

The main objective of the present paper is to determine the optimal trajectory of very flexible link manipulators in point-to-point motion using a new displacement approach. A new nonlinear finite element model for the dynamic analysis is employed to describe nonlinear modeling for three-dimensional flexible link manipulators, in which both the geometric elastic nonlinearity and the foreshortening effects are considered. In comparison to other large deformation formulations, the motion equations contain constant stiffness matrix because the terms arising from geometric elastic nonlinearity are moved from elastic forces to inertial, reactive and external forces, which are originally nonlinear. This makes the formulation particularly efficient in computational terms and numerically more stable than alternative geometrically nonlinear formulations based on lower-order terms. In this investigation, the computational method to solve the trajectory planning problem is based on the indirect solution of open-loop optimal control problem. The Pontryagin’s minimum principle is used to obtain the optimality conditions, which is lead to a standard form of a two-point boundary value problem. The proposed approach has been implemented and tested on a single-link very flexible arm and optimal paths with minimum effort and minimum vibration are obtained. The results illustrate the power and efficiency of the method to overcome the high nonlinearity nature of the problem.     

Stability analysis and robust composite controller synthesis for flexible joint robots

In this paper the control of flexible joint manipulators is studied in detail. The model of N-axis flexible joint manipulators is derived and reformulated in the form of singular perturbation theory and an integral manifold is used to separate fast dynamics from slow dynamics. A composite control algorithm is proposed for the flexible joint robots, which consists of two main parts. Fast control, u _f, guarantees that the fast dynamics remains asymptotically stable and the corresponding integral manifold remains invariant. Slow control, u _s, consists of a robust PID designed based on the rigid model and a corrective term designed based on the reduced flexible model. The stability of the fast dynamics and robust stability of the PID scheme are analyzed separately, and finally, the closed-loop system is proved to be uniformly ultimately bounded (UUB) stable by Lyapunov stability analysis. Finally, the effectiveness of the proposed control law is verified through simulations. The simulation results of single- and two-link flexible joint manipulators are compared with the literature. It is shown that the proposed control law ensures robust stability and performance despite the modeling uncertainties.     

Neural-network-based robust fault diagnosis in robotic systems

Fault diagnosis plays an important role in the operation of modern robotic systems. A number of researchers have proposed fault diagnosis architectures for robotic manipulators using the model-based analytical redundancy approach. One of the key issues in the design of such fault diagnosis schemes is the effect of modeling uncertainties on their performance. This paper investigates the problem of fault diagnosis in rigid-link robotic manipulators with modeling uncertainties. A learning architecture with sigmoidal neural networks is used to monitor the robotic system for any off-nominal behavior due to faults. The robustness and stability properties of the fault diagnosis scheme are rigorously established. Simulation examples are presented to illustrate the ability of the neural-network-based robust fault diagnosis scheme to detect and accommodate faults in a two-link robotic manipulator.