Dynamic modelling and parameter identification of a 3-DOF flight simulator platform

Dynamic models play a critical role in the design of model-based controllers, which has a significant effect on the dynamic characteristics of motion equipment. This paper mainly focuses on the dynamic modeling and parameter identification for a gantry-type automated fiber placement (AFP) machine. First, a dynamic modeling process combining prismatic axes and revolute axes is conducted by Newton-Euler method, in which the effects of friction and hydraulic balance system are also considered. Then, as the convenience for parameter identification and the application in linearity control, the methods of dynamic model linearization and determination of minimum inertial parameters based on the multi-body system (MBS) theory are proposed, with which a dynamic model in the form of linearized minimum inertial parameters is consequently established. To identify the parameters in the model, key issues regarding excitation trajectory, filtering, and identification algorithm are discussed in detail. Finally, corresponding experiments are performed on the AFP machine, and experimental results show that there is a good agreement between the prediction of the model and the measurement in actuality. Data analysis shows that except for Z-axis, the relative error rates of the others are not greater than 5%, which proves the effectiveness of the established dynamic model and the identified parameters.

Offline robot dynamic identification methods are based on the use of the inverse dynamic identification model (IDIM), which calculates the joint forces/torques (estimated as the product of the known control signal (the input reference of the motor current loop) with the joint drive gains) that are linear in relation to the dynamic parameters, and on the use of the linear least squares technique to calculate the parameters (IDIM-LS technique). However, as actuation-redundant parallel robots are overactuated, their IDIM has an infinity of solution for the force/torque prediction, depending on the value of the desired overconstraint that is a priori unknown in the identification process. As a result, the IDIM cannot be used as it is for such a class of parallel robots. This paper proposes a procedure for the dynamic parameter identification of actuation-redundant parallel robots. The procedure takes advantage of two possible modified formulations for the IDIM of actuation-redundant robots that can be used for identification purpose. The modified IDIM formulations project some or all input torques/forces onto the robot bodies, thus leading to a unique solution of the model that can then be used in the identification process. A systematic and straightforward way to compute these modified IDIM is presented. The identification of the inertial parameters of a planar parallel robot with actuation redundancy, the DualV, is then carried out using these modified IDIM. Experimental results show the validity of the methods.

Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual’s judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control.

Off-line dynamic identification requires the use of a model linear in relation to the robot dynamic parameters and the use of linear least squares technique to calculate the parameters. Most of time, the used model is the Inverse Dynamic Identification Model (IDIM). However, the computation of its symbolic expressions is extremely tedious. In order to simplify the procedure, the use of the Power Identification Model (PIM), which is dramatically simpler to obtain and that contains exactly the same dynamic parameters as the IDIM, was previously proposed. However, even if the identification of the PIM parameters for a 2 degrees-of-freedom (DOF) planar serial robot was successful, its fails to work for 6 DOF industrial robots. This paper discloses the reasons of this failure and presents a methodology for the identification of the robot dynamic parameters using the PIM. The method is experimentally validated on an industrial 6 DOF Stäubli TX-40 robot.

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.

Identification of dynamic parameters and feedforward control for a conventional industrial manipulator

This paper presents a new hybrid method, which integrates the structured laser light, decoupled dynamic models, and evolutionary optimization strategy, to identify dynamic parameters of autonomous underwater vehicles. This is the first research that investigates the utilization of laser scanned images for the system identification of underwater vehicles. The AUV’s equations of motions and the dynamic parameter identification using the AUV’s decoupled motions will be illustrated. The working principles to calculate the AUV’s positons using the structured laser light will be explained with respect to the surge and pitch motions. The evolutionary optimization strategy used to generate the AUV’s dynamic parameters will be presented.

Dynamic modeling and parameter identification for a gantry-type automated fiber placement machine combined with hydraulic balance system and nonlinear friction

A common issue of the parallel robot is that has a large number of dynamic parameters, which requires a lot of processing time, whether in dynamic modeling, identification or control. The optimization and estimation of inertial parameters of a large DoF number of robotic system is crucial to tune the model-based control law in order to improve the robot accuracy. In this paper, we present an optimized number of dynamic parameters, called base inertial parameters. As a result, only 90 base inertial parameters affect the evr@ simulator instead of 210 standard one. Torque signals evaluation from experimental parallel platform and the developed analytical form show the effectiveness of the obtained results.

Aiming at the shortcomings of the current dynamic parameter identification methods in fitting nonlinear friction characteristics, the satisfaction of physically-consistent constraints, and the efficiency of dynamic calculation of the minimum inertial set, a physical consistent dynamic full parameter identification method based on the nonlinear friction model is proposed. Firstly, according to the characteristics of each component of the robot's dynamic equation, the joint trajectory that can cancel the non-friction moment term during the forward and reverse rotation of the joint is designed, and the friction moment is separated from the measured moment; Secondly, the nonlinear friction model is used to model the friction torque, and the friction parameters are obtained by solving the nonlinear least square problem; Finally, the regularized weighted least squares problem with physically-consistent constraints is solved by convex optimization method, and the full parameter set of robot dynamics including friction parameters and inertia parameters is obtained. The experimental results show that the RMS error of the proposed dynamic parameter identification method is the smallest compared with the CAD numerical calculation method and the penalty optimization identification method.

摘要: 围绕护理机器人的人机安全接触和轻量大负载需求,提出了一种2R耦合驱动关节构型,并解决了耦合驱动动力学建模问题,为高性能运动控制器搭建提供基础。该关节设计紧凑、负载能力强,两个伺服电机经过三级减速后,通过差动结构实现两自由度耦合输出,且表面光滑适宜与人接触。通过运动学分析了耦合驱动的原理,利用拉格朗日法建立了耦合驱动动力学模型。为解决速度零点摩擦力不连续,造成基于模型的控制器运动性能变差的问题,引入了连续可微摩擦模型,利用连续可微特性采用灰色模型提高了辨识精度。研制了机器人关节样机,进行了关节解耦、摩擦数据采集、参数辨识及轨迹跟踪等试验,结果表明所设计的耦合驱动关节可以完成周转、俯仰两个转动自由度的单独及耦合运动,并且输出扭矩与重量的比值达到了143.6 N·m/kg,可以满足轻量大负载护理需求,同时基于所建立动力学模型的运动控制可以显著提高轨迹跟踪的准确性。

Hydraulic manipulators are favored because of their high power density and strong explosive force. As more tasks interact with the environment, better force/motion control performance is demanded. However, hydraulic manipulators are usually driven by closed kinematic loops containing linear hydraulic actuators with passive resolute joints, leading to the difficulty in full dynamic modeling and parameter identification for accurate model-based force/motion control. To overcome this problem, a cylinder separated model is proposed with hydraulic cylinders separated virtually through the concept of virtual equivalent rotational joints. The decoupling model describes the complex dynamics of closed-chain structures based on the Lagrange equation, which is used to identify both inertial parameters of rigid links and cylinders in addition. Besides, a hierarchical decoupling controller is designed by splitting hydraulic cylinder control from the manipulator dynamics on the basis of the decoupling model, and then, the control problems of structure mechanisms and hydraulic system are handled independently. Based on the proposed dynamic model and control strategy, contact force/motion control is realized with the contact force estimated from cylinder pressure sensors. Experiments reveal that the position error of the end effector is reduced at least by 12.7% compared with the conventional controller that ignores coupling problems, whereas the root mean square error of contact force is within 100 N. The proposed strategy shows satisfied performance for hydraulic manipulators, which is also convenient to implement.

In this paper we outline the design and parameter identification of a low-cost compass-gait bipedal robot for dynamic walking experiments. A compass gait walker exhibits a desirable balance of complexity in the dynamics and mechanical simplicity, making it a good candidate for a physical realization. In the hope of making the hardware of such walking robot more accessible to other researchers, we describe the the mechanical design, the software interface, as well as the dynamic modelling and parameter identification of a planar compass gait walker. Controlled walking experiments have also been performed to validate our model.

In terms of the heavy load and low viscosity operation conditions of the marine rim-driven thruster (RDT), a novel Magnetic Liquid-double-suspension Elastic-supported Thrust Bearing (MLETB) is designed. The MLETB combines the structural features of the Rubber-supported Water-lubricated Thrust Bearing (RWTB) and Permanent Magnet Bearing (PMB). To investigate the axial stiffness and damping of the bearing, the dynamic model of MLETB incorporating a multi-layer structure is developed. Simulation indicates that the dynamic performance of the MLETB is close to that of the RWTB, but the load capacity of the MLETB is better. Besides, the load is not the most important factor to affect the dynamic performance. The parameter identification method is proposed to analyze the experiment results based on the water-lubricated bearing test rig, which show that the MLETB has a dilemma between the load capacity and dynamic performance that its stiffness and damping will be seriously affected by the specific rubber structure.

The characterization and monitoring of buildings is an issue that has attracted the interest of many sectors over the last two decades. With the increasing use of permanent, continuous and real-time networks, ambient vibrations can provide a simple tool for the identification of dynamic building parameters. This study is focused on the long-term variation of frequency and damping in several buildings, using the Random Decrement Technique (RDT). RDT provides a fast, robust and accurate long-term analysis and improves the reliability of frequency and damping measurements for structural health monitoring. This reveals particularly useful information in finding out precisely how far changes in modal parameters can be related to changes in physical properties. This paper highlights the reversible changes of the structure's dynamic parameters, correlated with external forces, such as temperature and exposure to the sun. Contrasting behaviors are observed, including correlation and anti-correlation with temperature variations.