有色噪声条件下的子空间辨识改进方法及应用

针对工业生产过程中噪声往往为有色噪声的情况,提出一种改进的子空间辨识方法。传统的子空间辨识方法在系统存在有色噪声时辨识效果不佳,改进方法则采用变换系统模型形式来克服有色噪声对系统的影响,在辨识时直接利用变换系统模型后的数据得到系统较为准确的状态空间模型,实践证明,状态空间模型更适用于工业过程。连续搅拌反应釜（CSTR）系统是一类典型的工业生产系统,将子空间辨识方法应用于CSTR过程的仿真实验,通过比较改进前和改进后的系统预测误差,验证了所提方法的有效性。     

Combination of geometric and parametric approaches for kinematic identification of an industrial robot

Combination of geometric and parametric approaches of kinematic identification is proposed in this article. The experimental strategy is similar to that used in geometric approach wherein each axis of the robot is actuated one after the other. This adds clarity to experimental strategy, which becomes ambiguous while solely using a conventional parametric approach. Therefore it is easier to conduct experiments even if there are restrictions in workspace. The estimation was done using a parametric technique, but in a stage wise manner using a divide and conquer strategy. This allowed measurement of the robot accuracy after removing the errors arising due to the definition of base and end-effector frames. Additionally it is possible to visualize the reduction in errors during the estimation process. In addition to this, the Jacobian matrix that relates the pose errors to the correction in parameters is adapted during estimation using a damped least squares method depending upon the convergence of the parameters. Results were obtained after extensive experiments on industrial robots using three different measurement instruments namely laser tracker, monocular camera and multi-camera system. The proposed method performs better than the conventional approach which uses only geometric approach. Finally thanks to the new approach, it was possible to conduct experiments after dividing the workspace region into those with high and low levels of observability; which is not easy while using conventional approaches. It was also possible to perform identification in regions closer and farther away from the robot where there is deterioration of observability. The results show that the proposed method could reduce the errors in pose in a consistent manner, even when different measurement instruments were used, or when there was a deterioration in observability due to the choice of poses during identification.     

基于随机分布理论的递推子空间辨识

在实际生产过程中,采用传统子空间辨识法建立的离线模型并不能有效准确地跟踪系统的动态变化;奇异值分解等线性代数工具虽然增加算法的数值鲁棒性,但也相应增加了子空间辨识的在线递推困难.为解决上述问题,本文针对连续时间系统提出基于随机分布理论的递推子空间辨识方法.首先,通过随机分布理论构建系统的连续随机分布函数,并利用微分计算获得系统等价的输入输出矩阵方程.然后,采用将输入输出数据矩阵"R"规模固定的方法,达到数据压缩的目的.最后,通过最小二乘法和残差分析法递推更新模型的系统矩阵和噪声强度直至达到辨识要求.仿真结果验证了所提方法的有效性和精确性.     

Modelling the dynamics of industrial robots for milling operations

Using industrial robots as machine tools is targeted by many industries for their lower cost and larger workspace. Nevertheless, performance of industrial robots is limited due to their mechanical structure involving rotational joints with a lower stiffness. As a consequence, vibration instabilities, known as chatter, are more likely to appear in industrial robots than in conventional machine tools. Commonly, chatter is avoided by using stability lobe diagrams to determine the stable combinations of axial depth of cut and spindle speed. Although the computation of stability lobes in conventional machine tools is a well-studied subject, developing them in robotic milling is challenging because of the lack of accurate multi-body dynamics models involving joint compliance able of predicting the posture-dependent dynamics of the robot. In this paper, two multi-body dynamics models of articulated industrial robots suitable for machining applications are presented. The link and rotor inertias along with the joint stiffness and damping parameters of the developed models are identified using a combination of multiple-input multiple-output identification approach, computer-aided design model of the robot, and experimental modal analysis. The performance of the developed models in predicting posture-dependent dynamics of a KUKA KR90 R3100 robotic arm is studied experimentally.     

Improved closed-loop subspace identification with prior information

It has been proven that combining open-loop subspace identification with prior information can promote the accuracy of obtaining state-space models. In this study, prior information is exploited to improve the accuracy of closed-loop subspace identification. The proposed approach initially removes the correlation between future input and past innovation, a significant obstacle in closed-loop subspace identification method. Then, each row of the extended subspace matrix equation is considered an optimal multi-step ahead predictor and prior information is expressed in the form of equality constraints. The constrained least squares method is used to obtain improved results, so that the accuracy of the closed-loop subspace can be enhanced. Simulation examples are provided to demonstrate the effectiveness of the proposed algorithm.     

有色噪声背景下的正交子空间辨识

针对传统子空间辨识中存在的有色噪声干扰问题,本文提出一种正交子空间辨识方法.首先,根据子空间辨识算法机制构建含有色噪声的扩展状态空间模型.然后,结合有色噪声的相关性分析,研究了传统子空间辨识方法的有偏性问题,并重新设计了投影向量和正交投影方式,用以消除有色噪声干扰.最后,对投影后的数据矩阵进行奇异值分解,获取广义能观测矩阵,进而求得系统的状态空间模型参数.仿真结果表明该方法在有色噪声干扰下是一致无偏的,并且具有渐进二阶统计特性.结合陀螺仪的具体实验结果表明,该算法在实际应用中具有比传统子空间辨识法更高的辨识精度.     

线性时变反馈系统的状态空间模型和模态参数递推辨识

针对闭环系统中时变状态空间模型和模态参数的辨识问题, 提出一种递推辨识格式, 将这种格式与递推子空间方法结合, 得到一种辨识方法. 该方法通过重建输入输出数据之间的关系, 递推辨识得到闭环系统的时变状态空间模型和模态参数. 算例研究了系统在模态参数突变和周期变化两种情况下的辨识问题, 仿真结果表明, 所提出算法能有效辨识线性时变反馈系统的状态空间模型和模态参数.

     

Accurate dynamic modeling and control parameters design of an industrial hybrid spray-painting robot

To obtain higher performance for hybrid robots subject to nonlinear dynamics and friction, feedforward compensations have been ubiquitously utilized in the industrial robotic field to attenuate these disturbances. However, due to the complex friction model and the coupling and time-varying dynamic of hybrid robots, there is no effective approach to realize accurate feedforward compensations in industrial control systems. This paper investigated an accurate dynamic modeling and control parameters design method to address these issues all at once. Taking the friction of each joint into account, the accurate dynamic model of the hybrid robot is developed and verified by experiments. With the accurate dynamic model, an exact control parameter design method is proposed based on the mapping relationship between the dynamic model and the feedforward compensations. Additionally, the control system designed by the method proposed in this paper is compared with the one tuned by an experienced engineer. Particularly, the robot's position and motion accuracy are also tested by a third-party inspection agency. The experimental and test results show that the position and velocity accuracy of the robot is improved significantly when the control system is designed by using the method proposed in this paper, which proves the effectiveness of the proposed method.     

基于滑动拟合阶次和统计方法的模态阻尼比辨识技术

针对在使用环境激励进行模态辨识时,模态阻尼比辨识结果散布较大的问题,提出基于滑动拟合阶次与统计方法结合的模态阻尼比辨识方法,作为特征系统实现算法（Eigensystem Realization Algorithm,ERA）的前后处理方法,从而提高模态阻尼比的辨识精度和稳定性.详细介绍ERA环境激励模态辨识理论;给出滑动拟合阶次与统计方法相结合的模态阻尼比辨识方法以及流程.通过算例验证该方法的有效性.     

机器人减速器传动误差建模与优化

为提高工业机器人旋转矢量(RV)减速器的传动精度,合理分配各零件的加工和装配公差,本文提出一种基于等价模型的RV减速器传动误差建模与优化方法.该方法根据RV减速器的传动结构,构建17自由度的等价误差模型,利用传统经验参数进行求解,获得减速器仿真传动误差;同时,将仿真传动误差与实际测量传动误差进行对比,运用最小二乘法建立经验参数辨识模型;在此基础上通过粒子群算法优化辨识模型中的经验参数,将该参数运用到实际RV减速器生产中,结果显示:与传统经验参数建立的误差模型相比,本文提出的方法使得传动精度的仿真精度误差平均缩小9.99%,大幅度提高了等价误差模型的准确性.     

Revolute manipulator workspace optimization: A comparative study

Robotic manipulators with three revolute families of positional configurations are very common in the industrial robots. The capability of a robot largely depends on the workspace of the manipulator apart from other parameters. In this work, an evolutionary optimization algorithm based on foraging behavior of Escherichia coli bacteria present in human intestine is utilized to optimize the workspace volume of a 3R manipulator. The proposed optimization method is subjected to some modifications for faster convergence than the original algorithm. Further, the method is also very useful in optimization problems in a highly constrained environment such as the robot workspace optimization. The test results are compared with standard results available using other optimization algorithms such as Differential Evolution, Genetic Algorithm and Particle Swarm Optimization. In addition, this work extends the application of the proposed algorithm to two different industrial robots. An important implication of this paper is that the present algorithm is found to be superior to other methods in terms of computational efficiency.     

A two-step method for kinematic parameters calibration based on complete pose measurement—Verification on a heavy-duty robot

The poor pose accuracy of industrial robots restricts their further application in aviation manufacturing. Kinematic calibration based on position errors is a traditional method to improve robot accuracy. However, due to the difference between length errors and angle errors in the order of magnitude, it is difficult to accurately calibrate these geometric parameters together. In this paper, a two-step method for robot kinematic parameters calibration and a novel method for position and orientation measurement are proposed and combined to identify these two kinds of errors respectively. The redundant parameter errors that affect the identification are also analyzed and eliminated to further improve the accuracy of this two-step method. Taking the Levenberg-Marquardt algorithm as the underlying algorithm, simulation results indicate that the proposed two-step calibration method has faster iteration speed and higher identification accuracy than the traditional one. On this basis, the calibration and measurement methods proposed in this paper are verified on a heavy-duty robot used for fiber placement. Experimental results show that the mean absolute position error decreases from 0.9906 mm to 0.3703 mm after calibration by the proposed two-step calibration method with redundancy elimination. The absolute position accuracy has increased by 41.81% compared with the traditional method based on position errors only and 14.97% compared with the two-step calibration method without redundancy elimination. At the same time, the orientation errors after calibration are not more than 0.1485°, and the average of absolute errors is 0.0447.     

Sensorless force estimation for industrial robots using disturbance observer and neural learning of friction approximation

Contact force estimation enables robots to physically interact with unknown environments and to work with human operators in a shared workspace. Most heavy-duty industrial robots without built-in force/torque sensors rely on the inverse dynamics for the sensorless force estimation. However, this scheme suffers from the serious model uncertainty induced by the nonnegligible noise in the estimation process. This paper proposes a sensorless scheme to estimate the unknown contact force induced by the physical interaction with robots. The model-based identification scheme is initially used to obtain dynamic parameters. Then, neural learning of friction approximation is designed to enhance estimation performance for robotic systems subject with the model uncertainty. The external force exerted on the robot is estimated by a disturbance observer which models the external disturbance. A momentum observer is modified to develop a disturbance Kalman filter-based approach for estimating the contact force. The neural network-based model uncertainty and measurement noise level are analysed to guarantee the robustness of the Kalman filter-based force observer. The proposed scheme is verified by the measurement data from a heavy-duty industrial robot with 6 degrees of freedom (KUKA AUGLIS six). The experimental results are used to demonstrate the estimation performance of the proposed approach by the comparison with the existing schemes.     

A Simple and Novel Hybrid Robotic System for Robot-Assisted Femur Fracture Reduction

When performing femur fracture reduction surgery, both the patient and surgeon are exposed to a great amount of radiation, which is harmful to their health. In order to reduce such radiation from the usage of an image intensifier, various robots have been proposed for femur fracture reduction surgery. Most of these robots are based on serial architecture. The low transportable load and poor accuracy are both inherent in serial robots, which makes them inappropriate for femur fracture reduction. Some parallel robots based on the 'Stewart platform' have also been developed for femur fracture reduction, but their restricted workspace limits their applicability and accessibility. To balance the accuracy, payload and workspace, a new robot system is reported in this paper. The proposed robot system consists of a 2-d.o.f. device and a 6-d.o.f. hybrid robot. The 2-d.o.f. device is used for distraction, which requires a very large force. The hybrid robot is used to manipulate a bone fragment for alignment and fixation purposes. The hybrid robot possesses the characteristic of a Cartesian coordinate robot; all the movements of the actuators are linear, which makes its motion smooth for low-speed fracture reduction procedures. The forward and inverse kinematics of the proposed robot are analyzed. The analysis is much simpler compared to traditional serial manipulators and parallel Stewart platform robots. A prototype of the proposed system is made using a rapid fabrication system called Objet. The positioning accuracy of the proposed system is measured using a coordinate-measuring machine. The results show that the algorithms presented in this paper for the control of the robot are accurate and robust.     

A novel XY-Theta precision table and a geometric procedure for its kinematic calibration

Spatial precision positioning devices are often based on parallel robots, but when it comes to planar positioning, the well-known serial architecture is virtually the only solution available to industry. Problems with parallel robots are that most are coupled, more difficult to control than serial robots, and have a small workspace. In this paper, new parallel robot is proposed, which can deliver accurate movements, is partially decoupled and has a relatively large workspace. The novelty of this parallel robot lies in its ability to achieve the decoupled state by employing legs of a different kinematic structure. The robot repeatability is evaluated using a CMM and so are the actual lead errors of its actuators. A simple geometric method is proposed for directly identifying the actual base and mobile reference frames, two actuator's offsets and one distance parameter, using a measurement arm from FARO Technologies. While this method is certainly not the most efficient one, it yields a satisfactory improvement of the robot accuracy without the need for any background in robot calibration. An experimental validation shows that the position accuracy achieved after calibration is better than 0.339 mm within a workspace of approximately 150 mm×200 mm.     

基于腕力传感器的机器人操作臂惯性参数辨识方法

针对工业机器人结构设计及动力控制中，在比现有方法少用了基座力传感器的基础上，充分挖掘了腕力传感器的信息，利用机械臂运动学及动力学递推关系，由Newton-Euler方程导出了各连杆惯性参数逆向的辨识模型．以一个算例说明了方法的运用，为机器人操作臂动力学建模提供了理论基础．     

Maximum DLCC of Spatial Cable Robot for a Predefined Trajectory Within the Workspace Using Closed Loop Optimal Control Approach

One of the most important applications of cable robots is load carrying along a specific path. Control procedure of cable robots is more challenging compared to linkage robots since cables can’t afford pressure. Meanwhile carrying the heaviest possible payload for this kind of robots is desired. In this paper a nonlinear optimal control is proposed in order to control the end-effector within a predefined trajectory while the highest Dynamic Load Carrying Capacity (DLCC) can be carried. This purpose is met by applying optimum torque distribution among the motors with acceptable tracking accuracy. Besides, other algorithms are applied to make sure that the allowable workspace constraint is also satisfied. Since the dynamics of the robot is nonlinear, feedback linearization approach is employed in order to control the end-effector on its desirable path in a closed loop way while Linear Quadratic Regulator (LOR) method is used in order to optimize its controlling gains since the state space is linearized by the feedback linearization. The proposed algorithm is supported by doing some simulation studies on a two Degrees of Freedom (DOF) constrained planar cable robot as well as a six DOFs under constrained cable suspended robot and their DLCCs are calculated by satisfying the motor torque, tracking error and allowable workspace constraints. The results including the angular velocity, motors’ torque, actual tracking of the end-effector and the DLCC of the robot are calculated and verified using experimental tests done on the cable robot. Comparison of the results of open loop simulation results, closed loop simulation results and experimental tests, shows that the results are improved by applying the proposed algorithm. This is the result of tuning the motors’ torque and accuracy in a way that the highest DLCC can be achieved.     

Kinematic model identification of industrial manipulators

The aim of the work presented in this paper is to improve the off-line programming capability of industrial robots by improving their accuracy. Rather than impose more strict manufacturing tolerances, it is widely accepted that a method of identifying kinematic parameters specific to each individual robot provides a cost effective way of improving accuracy. A procedure is presented for identification of actual kinematic parameters, which uses the plane of rotation and centre of rotation introduced by Stone. The procedure differs from that of Stone in that it makes use of the radius of rotation and also introduces a translation of the plane of rotation along the axis of rotation. This allows for the direct identification of the D–H model parameters which are more widely accepted and easier to interpret than the S model parameters. It is shown that, unlike the original method of Stone, the new procedure can also deal with the situation when two consecutive joint axes are parallel. The method is validated on both simulated data and real measured data for a Puma 560 robot, showing an improvement in positioning accuracy of around 80%.     

An instrumental variable approach for rigid industrial robots identification

This paper deals with the important topic of rigid industrial robots identification. The usual identification method is based on the use of the inverse dynamic model and the least-squares technique. In order to obtain good results, a well-tuned derivative bandpass filtering of joint positions is needed to calculate the joint velocities and accelerations. However, we can doubt whether the bandpass filter is well-tuned or not. Another approach is the instrumental variable (IV) method which is robust to data filtering and which is statistically optimal. In this paper, an IV approach relevant for identification of rigid industrial robots is introduced. The set of instruments is the inverse dynamic model built from simulated data which are calculated from the simulation of the direct dynamic model. The simulation assumes the same reference trajectories and the same control structure for both the actual and the simulated robot and is based on the previous IV estimates. Furthermore, to obtain a rapid convergence, the gains of the simulated controller are updated according to IV estimates. Thus, the proposed approach validates the inverse and direct dynamic models simultaneously and is not sensitive to initial conditions. The experimental results obtained with a 2 degrees of freedom (DOF) planar prototype and with a 6 DOF industrial robot show the effectiveness of our approach: it is possible to identify 60 parameters in 3 iterations and in 11 s.     

Design parameter evaluation based on human operation for tip mechanism of forceps manipulator using surgical robot simulation

We proposed a design method for pediatric surgical robots that evaluates the workspace and view information in computer simulator before the actual robot is developed. In this study, we investigated a suturing task in a virtual environment using forceps manipulators with different mechanical parameters. We reproduced the surgical workspace for congenital esophageal atresia and measured the working volume and invisible area to obtain suitable parameters for the suturing task. We also calculated the suitable mechanical parameters using Pareto optimal solution method and verified the mechanical parameters in Pareto optimal solution. We verified from the experimental results that there is a trade-off between the working volume and invisible area during the suturing task. Moreover, we determined from the calculation results that the mechanical design of the forceps manipulator is influenced by the invisible area during the suturing task. Finally, we confirmed that it is possible to obtain suitable parameters for surgical robots using the proposed method.