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1 – 10 of over 1000Xiaofeng Liu, Bangzhao Zhou, Boyang Xiao and Guoping Cai
The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target.
Abstract
Purpose
The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target.
Design/methodology/approach
An inertia parameter identification method is proposed in the post-capture scenario in this paper. This method is to resolve parameter identification with two steps: coarse estimation and precise estimation. In the coarse estimation step, all the robot arms are fixed and inertia tensor of the combined system is first calculated by the angular momentum conservation equation of the system. Then, inertia parameters of the unknown target are estimated using the least square method. Second, in the precise estimation step, the robot arms are controlled to move and then inertia parameters are once again estimated by optimization method. In the process of optimization, the coarse estimation results are used as an initial value.
Findings
Numerical simulation results prove that the method presented in this paper is effective for identifying the inertia parameter of a captured unknown target.
Practical implications
The presented method can also be applied to identify the inertia parameter of space robot.
Originality/value
In the classic momentum-based identification method, the linear momentum and angular momentum of system, both considered to be conserved, are used to identify the parameter of system. If the elliptical orbit in space is considered, the conservation of linear momentum is wrong. In this paper, an identification based on the conservation of angular momentum and dynamics is presented. Compared with the classic momentum-based method, this method can get a more accurate identification result.
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Keywords
Zhiyu Ni, Yewei Zhang, Xinhui Shen, Shunan Wu and Zhigang Wu
When a manipulator captures an unknown space object, inertia parameters of endpoint payload should be timely obtained to handle possible unexpected parameter variations and…
Abstract
Purpose
When a manipulator captures an unknown space object, inertia parameters of endpoint payload should be timely obtained to handle possible unexpected parameter variations and monitor the system’s operating conditions. Therefore, this study aims to present an identification method for estimating the inertia parameter of the payload carried by a flexible two-link space manipulator.
Design/methodology/approach
The original nonlinear dynamics model of the manipulator is linearized at a selected working point. Subsequently, the system modal frequencies with and without payload are determined using the subspace identification algorithm, and the difference of these frequencies is computed. Furthermore, by adjusting the structural configuration of the manipulator, multiple sets of frequency differences are obtained. Therefore, the inertia parameters of the payload, i.e. the mass and the moment of inertia, can be derived from the frequency differences by solving a least-squares problem.
Findings
The proposed method can effectively estimate the payload parameters and has satisfactory identification accuracy.
Practical implications
The approach’s implementation provides a practical reference for determining inertia parameters of an unknown space target in the capture process.
Originality/value
The study proposes a novel method for identifying the inertia parameters of the payload of a flexible two-link space manipulator using the estimated system frequencies.
Details
Keywords
Juliang Xiao, Fan Zeng, Qiulong Zhang and Haitao Liu
This paper aims to propose a forcefree control algorithm that is based on a dynamic model with full torque compensation is proposed to improve the compliance and flexibility of…
Abstract
Purpose
This paper aims to propose a forcefree control algorithm that is based on a dynamic model with full torque compensation is proposed to improve the compliance and flexibility of the direct teaching of cooperative robots.
Design/methodology/approach
Dynamic parameters identification is performed first to obtain an accurate dynamic model. The identification process is divided into two steps to reduce the complexity of trajectory simplification, and each step contains two excitation trajectories for higher identification precision. A nonlinear friction model that considers the angular displacement and angular velocity of joints is proposed as a secondary compensation for identification. A torque compensation algorithm that is based on the Hogan impedance model is proposed, and the torque obtained by an impedance equation is regarded as the command torque, which can be adjusted. The compensatory torque, including gravity torque, inertia torque, friction torque and Coriolis torque, is added to the compensation to improve the effect of forcefree control.
Findings
The model improves the total accuracy of the dynamic model by approximately 20% after compensation. Compared with the traditional method, the results prove that the forcefree control algorithm can effectively reduce the drag force approximately 50% for direct teaching and realize a flexible and smooth drag.
Practical implications
The entire algorithm is verified by the laboratory-developed six degrees-of-freedom cooperative robot, and it can be applied to other robots as well.
Originality/value
A full torque compensation is performed after parameters identification, and a more accurate forcefree control is guaranteed. This allows the cooperative robot to be dragged more smoothly without external sensors.
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Keywords
Jian-jun Yuan, Weiwei Wan, Xiajun Fu, Shuai Wang and Ning Wang
This paper aims to propose a novel method to identify the parameters of robotic manipulators using the torque exerted by the robot joint motors (measured by current sensors).
Abstract
Purpose
This paper aims to propose a novel method to identify the parameters of robotic manipulators using the torque exerted by the robot joint motors (measured by current sensors).
Design/methodology/approach
Previous studies used additional sensors like force sensor and inertia measurement unit, or additional payload mounted on the end-effector to perform parameter identification. The settings of these previous works were complicated. They could only identify part of the parameters. This paper uses the torque exerted by each joint while performing Fourier periodic excited trajectories. It divides the parameters into a linear part and a non-linear part, and uses linear least square (LLS) parameter estimation and dual-swarm-based particle swarm optimization (DPso) to compute the linear and non-linear parts, respectively.
Findings
The settings are simpler and can identify the dynamic parameters, the viscous friction coefficients and the Coulomb friction coefficients of two joints at the same time. A SIASUN 7-Axis Flexible Robot is used to experimentally validate the proposal. Comparison between the predicted torque values and ground-truth values of the joints confirms the effectiveness of the method.
Originality/value
The proposed method identifies two joints at the same time with satisfying precision and high efficiency. The identification errors of joints do not accumulate.
Details
Keywords
The purpose of this paper is to develop a novel nonlinear H∞ control approach for the nonlinear multivariable attitude tracking of rigid spacecraft.
Abstract
Purpose
The purpose of this paper is to develop a novel nonlinear H∞ control approach for the nonlinear multivariable attitude tracking of rigid spacecraft.
Design/methodology/approach
Based on the transformation of the attitude tracking problem into quaternion error stabilization, the feedback control law is developed by using the normal matrix control theory with the inverse‐additive perturbation description of systems uncertainties, and the Hamilton‐Jacobi‐Isaacs (HJI) partial differential inequality is employed for providing the nonlinear H∞ control criteria for the proposed control law. The onboard recursive least squares (RLS) estimation algorithm of inertia tensor is used for the further improving of the normal matrix property of the control system. The RLS algorithm is simple enough for the spacecraft borne computer. Computer simulation is performed to demonstrate the effectiveness of the control law proposed.
Findings
By the normal matrix control theory, the nonlinear H∞ control law for attitude tracking is developed without solving the HJI inequality and with the inflight estimation of inertia, the proposed control law is adaptive and robust to the variation of mass properties, and its normality is further improved.
Research limitations/implications
The paper is limited in rigid spacecraft with slowly changing mass property. The flexible influences are not considered.
Practical implications
The paper provides an alternative to the spacecraft researchers/engineers for developing the robust attitude control law with a simple structure and self‐tuning ability.
Originality/value
The paper is the first to provide a robust control based on the normal matrix approach, the HJI inequality, and the estimation of inertia.
Details
Keywords
Angel Flores-Abad, Pu Xie, Gabriela Martinez-Arredondo and Ou Ma
– Calibration and 6-DOF test of a unique inertial measurement unit (IMU) using a Quadrotor aircraft. The purpose of this paper is to discuss the above issue.
Abstract
Purpose
Calibration and 6-DOF test of a unique inertial measurement unit (IMU) using a Quadrotor aircraft. The purpose of this paper is to discuss the above issue.
Design/methodology/approach
An IMU with the special capability of measuring the angular acceleration was developed and tested. A Quadrotor aircraft is used as 6-DOF test platform. Kinematics modeling of the Quadrotor was used in the determination of the Euler angles, while Dynamics modeling aided in the design the closed loop controller. For safety, the flight test was performed on a 6-DOF constrained reduced-gravity test stand.
Findings
The developed IMU is suitable for measuring states and its time derivatives of mini UAVs. Not only that but also a simple control algorithm can be integrated in the same processing unit (a 32 microcontroller in this case).
Originality/value
The tested IMU as well as the safety constrained test techniques are unique.
Shuanggao Li, Wenmin Chu and Xiang Huang
The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of…
Abstract
Purpose
The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of aircraft barycenter, the posture of the aircraft needs to be adjusted manually and is measured by optical instruments. The efficiency of posture adjustment depends on the proficiency of workers, and the accuracy of measurement is not high. In view of these problems of the current barycenter measurement method, this paper aims to propose an aircraft barycenter measurement method based on multi-posture.
Design/methodology/approach
In this method, the numerical control locator is used as a supporting part to fix and adjust the aircraft, and the calculation model of aircraft barycenter is established according to the principle of rigid body rotation and the principle of moment balance. Then, the influence of the main error sources on the measurement accuracy of aircraft barycenter is analyzed by Monte Carlo simulation, and the measurement accuracy is compared with that of the barycenter measurement method based on horizontal posture. Finally, the experiment platform of barycenter measurement was built in the laboratory and the experiments were carried out.
Findings
The experimental results show that the barycenter measurement method proposed in this paper has obvious advantages in measurement accuracy and efficiency compared with the traditional method.
Originality/value
This method can be used to measure the barycenter of different types of aircraft quickly and automatically.
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Yunfei Dong, Tianyu Ren, Ken Chen and Dan Wu
This paper aims to improve the accuracy of robot payload identification and decrease the complexity in its industrial application by developing a new method based on the actuator…
Abstract
Purpose
This paper aims to improve the accuracy of robot payload identification and decrease the complexity in its industrial application by developing a new method based on the actuator current.
Design/methodology/approach
Instead of previous general robot dynamic modeling of the actuators, links, together with payload inertial parameters, the paper discovers that the difference of the actuator torque between the robot moving along the same trajectory with and without carrying payload can be described as a function of the payload inertial parameters directly. Then a direct dynamic identification model of payload is built, a set of specialized novel exciting trajectories are designed for accurate identification and the least square method is applied for the estimation of the load parameters.
Findings
The experiments confirm the effectiveness of the proposed method in robot payload identification. The identification accuracy is greatly improved compared with that of existing methods based on the actuator current and is close to the accuracy of the methods that direct use the wrist-mounted force-torque sensor.
Practical implications
As the provided experiments indicate, the proposed method expands the application range and greatly improves the accuracy, hence making payload identification fully operational in the industrial application.
Originality/value
The novelty of such an identification method is that it does not require the rotor inertias and inertial parameters of links as a prior knowledge, and the specially designed trajectories provide completed decoupling of the load parameters.
Details
Keywords
Feifei Zhong, Guoping Liu, Zhenyu Lu, Lingyan Hu, Yangyang Han, Yusong Xiao and Xinrui Zhang
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by…
Abstract
Purpose
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.
Design/methodology/approach
This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.
Findings
Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.
Originality/value
A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.
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Keywords
Youshuang Ding, Xi Xiao, Xuanrui Huang and Jiexiang Sun
This paper aims to propose a novel system identification and resonance suppression strategy for motor-driven system with high-order flexible manipulator.
Abstract
Purpose
This paper aims to propose a novel system identification and resonance suppression strategy for motor-driven system with high-order flexible manipulator.
Design/methodology/approach
In this paper, first, a unified mathematical model is proposed to describe both the flexible joints and the flexible link system. Then to suppress the resonance brought by the system flexibility, a model based high-order notch filter controller is proposed. To get the true value of the parameters of the high-order flexible manipulator system, a fuzzy-Kalman filter-based two-step system identification algorithm is proposed.
Findings
Compared to the traditional system identification algorithm, the proposed two-step system identification algorithm can accurately identify the unknown parameters of the high order flexible manipulator system with high dynamic response. The performance of the two-step system identification algorithm and the model-based high-order notch filter is verified via simulation and experimental results.
Originality/value
The proposed system identification method can identify the system parameters with both high accuracy and high dynamic response. With the proposed system identification and model-based controller, the positioning accuracy of the flexible manipulator can be greatly improved.
Details