Industrial robot track modeling and vibration suppression

Energy Efficient Trajectories for an Industrial ABB Robot

Dynamic modeling and vibration prediction of an industrial robot in manufacturing

To obtain higher performance for an industrial hybrid robot, the dynamic control method is utilized to control the robot. For dynamic control, the control performance is directly affected by the accuracy of the dynamic model. This paper investigated a method to establish and identify an accurate dynamic model. First, based on the Lagrangian dynamic equation and the Stribeck friction model, the unidentified dynamic model of the five-DOF hybrid robot is established. Second, identification experiments are carried out. Each of the driving joints performs frequent reciprocating motions individually. In the meantime, the moving speed is gradually increased to obtain driving torques of the respective joint at different moving speeds. Then the dynamic parameters with lower coupling are identified by using the standard deviation index and the least squares methods until all parameters are gradually determined. Finally, the hybrid robot moves a typical trajectory, while the currents of each joint are collected to obtain the driving forces. The actual driving forces, the identified dynamic model, and the unidentified dynamic model are compared. The results show that the identified method could significantly improve the accuracy of the dynamic model. The method proposed in this paper is general and can be applied to the other robots without adding any sensors.

In this paper, a practical method is proposed to suppress residual vibrations of industrial robots without a real-time estimation of vibration frequencies. Through theoretical analysis and experiments, we designed an input shaping technique (IST) for the first three axes of a six-degrees-of-freedom industrial robot. Iterative learning IST (LIST) is applied to the first axis to suppress its time-varying nonlinear residual vibration, while conventional IST is applied to the second and third axes. Experimental results show that LIST can suppress residual vibrations to a level similar to that of a time-varying IST which requires complicated real-time estimation of a dynamic model. The LIST is an attractive method for suppression of nonlinear and time-varying residual vibrations in industrial robots which perform repetitive tasks because most industrial robots have limited computing power and memory space in their controllers.

A deterministic model for the transmission dynamics of melioidosis disease in human population is designed and analyzed. The model is shown to exhibit the phenomenon of backward bifurcation, where a stable disease-free equilibrium co-exists with a stable endemic equilibrium when the basic reproduction number [Formula: see text] is less than one. It is further shown that the backward bifurcation dynamics is caused by the reinfection of individuals who recovered from the disease and relapse. The existence of backward bifurcation implies that bringing down [Formula: see text] to less than unity is not enough for disease eradication. In the absence of backward bifurcation, the global asymptotic stability of the disease-free equilibrium is shown whenever [Formula: see text]. For [Formula: see text], the existence of at least one locally asymptotically stable endemic equilibrium is shown. Sensitivity analysis of the model, using the parameters relevant to the transmission dynamics of the melioidosis disease, is discussed. Numerical experiments are presented to support the theoretical analysis of the model. In the numerical experimentations, it has been observed that screening and treating individuals in the exposed class has a significant impact on the disease dynamics.

<p indent=0mm>In the mission of spacecraft on-orbit assembly and service, a large flexible spacecraft combination will be formed by the capturing spacecraft and the target spacecraft after the space manipulator completes the capturing misssion. First, taking comprehensive consideration of vibration influence of all the flexible components as the joints, links and solar arrays, the dynamic model of the spacecraft combination is established. The non-linear torsional spring models are adopted for flexible joints description; the assumed mode method and the finite element method are adopted for the flexible links and solar arrays; and the dynamic equation of the flexible spacecraft combination is established by use of the momentum conservation and the Lagrange equation. In addition, a composite controller of the flexible spacecraft combination is designed for trajectories tracking and vibration suppressing. The dynamic model of the flexible spacecraft combination is decomposed by use of the singular perturbation method and the two sub-controllers are designed seperately in two different time scales. Finally, the numerical simulations are carried out to verify the effectiveness of the modeling and control methods. The results illustrate that the dynamic model is accurate and effective for representing the kinematic and dynamic properties of the flexible spacecraft combination, and the composite control method is able to guarantee the trajectory tracking pricision as well as effective vibration suppression of the flexible components. The dynamic modeling and control method are applicable for engineering practice.

In this paper, we discuss the relation between liquidity and the business cycle.There are some reasons that we should link liquidity with the business cycle. The“flight to liquidity” or “flight to quality” hypothesis might be the most important one. It is more likely that an investor shifts his portfolio from those stocks with lower liquidity or higher risk when the economy is in a recession.Instead of business cycle measures, we use the NBER recession signal as the proxy of real economy. We apply dynamic and static probit model to monthly liquidity proxy, because the NBER recession is not always available in current period. Besides we use Amihud (2002) ILR as our liquidity proxy.The dynamic probit model with liquidity added does not result in a significance improvement on prediction. No matter in sample or out of sample, the pure dynamic probit model performs well with itself history only. However, as we mentioned earlier, NBER recession signal is usually announced well until the recession has happened for months, leading to an infeasibility to implement dynamic model. On the other hand, liquidity plays an important role in static probit model. We find a robust positive relation between liquidity and recession. Adding liquidity as a predictor in the static model would significantly improve the forecast accuracy in th short horizon. This observation remains robust with comparison to other financial variables ( e.g. term spread, credit spread, market volatility, and excess return). We also find the existence of “size effect” that small firm is more sensitive to future recession. Our finding above is consistent with our claims of “flight to liquidity; that is, it is more likely for market participants to shift his portfolio from those stock with lower liquidity or higher risk in advance when the economy would be in a recession. The primary contribution of this paper is that liquidity proxy, Amihud’s liquidity proxy here, does provide useful information when predicting the future recession. We find that the liquidity proxy performs well especially in a short prediction horizon. Besides, the liquidity of small firms is more informative in prediction.

Accurate prediction of non-premixed turbulent combustion using large eddy simulation (LES) requires detailed modelling of the mixing between fuel and oxidizer that occurs at scales smaller than the LES filterwidth. The small-scale mixing process can be quantitatively characterized by two related variables, the subfilter scalar variance and the subfilter scalar dissipation rate. A recently proposed alternative dynamic modelling procedure for the subfilter scale dissipation rate, designed for use with transport equation based models for subfilter scalar variance, is analysed in this work. This new dynamic non-equilibrium modelling approach produces a nonlinear interaction between variance and dissipation rate predictions that makes it difficult to isolate the performance of any single modelling component in a conventional LES simulation. To gain a better understanding of the new model, a three-part study is undertaken here. The first part of the study uses a priori analysis to examine some novel aspects of the model’s computation and guide its practical implementation. In the second part of the study, detailed a posteriori analysis of the model is performed. This analysis suggests that the dynamic estimate of the dissipation rate model coefficient helps to compensate for over-prediction of variance production rates and improves the accuracy of variance prediction. However, improved modelling of the variance production term, which in turn depends on the accuracy of models for the subfilter scalar flux, is necessary to allow both the scalar variance and dissipation rate to be predicted accurately. Therefore, the third part of the study examines the effect of the scalar flux model on the predictions of the dynamic non-equilibrium model. Use of a mixed model for the fluxes, rather than a gradient-diffusion-only model, is found to improve variance predictions in some cases.

Vibration control for large space truss structure assembly using a distributed adaptive neural network approach

To achieve high speed and high acceleration, flexible planar parallel manipulators (PPM) are typically designed with lightweight linkages, but hence suffer from unwanted structural vibration, diminishing positioning accuracy. This paper addresses the dynamic modeling and efficient modal control for vibration suppression of a PPM with three flexible linkages actuated by linear ultrasonic motors (LUSM). To achieve active vibration control, multiple lead zirconate titanate (PZT) transducers are mounted on the flexible links as vibration sensors and actuators. Based on Lagrange's equations, the dynamic model of the flexible links is derived with the dynamics of PZT actuators incorporated. Using the assumed mode method, the elastic motion of the flexible links are discretized under the assumptions of pinned-free boundary conditions, and the assumed mode shapes are validated through experimental modal test. Efficient modal control, in which the feedback forces in different modes are determined according to the vibration amplitude or energy of their own, is employed to control the PZT actuators to realize active vibration suppression. Computer simulations and vibration control experiments are conducted, and the results demonstrate that the presented dynamic model and the proposed active vibration control strategy are effective.

An analysis of dynamic Smagorinsky models is performed based on the Horizontal Array Turbulence Study (HATS) dataset. In the experiment, two vertically separated horizontal arrays of 14 three-dimensional sonic anemometers were placed in the atmospheric surface layer. Subgrid-scale (SGS) and resolved quantities are derived from 2D filtering at a filter scale Δ and differentiation of filtered velocity fields. In a previous study the Smagorinsky coefficient c(Δ)s was computed directly from these data and found to depend on atmospheric stability and height above the ground. The present study examines the scale-invariant dynamic model of Germano et al. and the scale-dependent dynamic model of Porté-Agel et al. and tests their accuracy in predicting c(Δ)s and its dependencies on stability and height above the ground. The Germano identity uses a test filter at αΔ (in this study α = 1.75 is used). The coefficient is derived from various data test-filtered at this scale assuming that the Smagorinsky coefficient is scale invariant. The results show that the scale-invariant dynamic model severely underpredicts the coefficient and its trends whenever Δ is similar to, or larger than, the large-scale limit of the inertial range (typically the smaller of the height above the ground z or the Obukhov length L). The scale-dependent dynamic model uses a second test filter at scale α2Δ to deduce dependence of c(Δ)s on the filtering scale. This model gives excellent predictions of c(Δ)s and its dependence upon stability and height.

This paper deals with two robot identification methods recently introduced. The first one is based on the use of the Inverse Dynamic Identification Model (IDIM) and the Instrumental Variable (IV). The second one is the Direct and Inverse Dynamic Identification Models (DIDIM) method, which is a closed-loop output error method minimizing the quadratic error between the actual and simulated joint torques. Both methods rely on the simulation of the Direct Dynamic Model (DDM). They are compared with a six degrees of freedom industrial robot. The experimental results show that the DIDIM method has the advantage of requiring less data preprocessing. Nevertheless, the IDIM-IV method appears to be more robust to modelling errors in the simulation which are not located in the identified dynamic model.

The robot arm used in these studies is shown. A DC motor is connected to a joint through a harmonic drive gear as a prime mover actuator. The timing belts are provided between the joints to drive a link along the X axis. In this mechanical system the flexibility of the timing belts produces vibrations. The robot arm with timing belts is modeled with consideration given to this flexibility. The appropriateness of the proposed mechanical model is examined based on computer simulations and experimental results. The model of the robot is derived from the Lagrangian equations and the flexible transmission is approximated as a torsional spring. A positioning servosystem with suppression of vibrations based on this mechanical model is presented. The performance of the proposed control system and the effect of the suppression of vibrations are examined based on the computer simulations and experimental results. >

This paper presents an improved S-curve motion profile to address vibration issues in industrial robots. While numerous studies have optimized motion commands based on the S-curve feedrate profile for vibration suppression, their performance in damped systems has often been suboptimal. To this end, the proposed profile integrates an improved S-curve feedrate motion with local input shaping to accelerate vibration attenuation. The design method is also introduced to minimize its total motion time. Compared with the optimized S-curve, and the time-optimal smooth S-curve, the proposed method based on the improved S-curve possesses superior vibration suppression capability. Furthermore, the improved S-curve achieves this with less time delay than the optimized smooth S-curve. Experimental validations on a serial industrial robot and a gantry platform confirm the practical effectiveness of the proposed motion profile in reducing vibrations, supporting its applicability in robotic systems.

Nowadays, most industrial robots have been designed to be mechanically stiff with rigid link. When a robot with heavy payload is running in fast motions, the residual vibrations of the end-effector are primary caused by joint flexibility. Therefore, the flexibility of joint cannot be neglected. This paper presents a systematic approach to dynamic modeling and residual vibration mode analysis for an industrial robot with rigid links and flexible joints (RLFJ). First, the flexibility of the joint is modeled as a torsional spring and the dynamic equations for this robot are derived by using Lagrange's method. Then, to examine residual vibration properties of the system, numerical simulation is carried out. The following important conclusions are drawn from simulation results: (1) the proposed dynamic model can represent joint flexibility of industrial robot and the joint flexibility causes the residual vibration of the end-effector; (2) for a given RLFJ model, the residual vibration is mainly affected by the payload mass, path of the task and joint stiffness.