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Article
Publication date: 27 December 2022

Salma Jnayah and Adel Khedher

The direct torque control (DTC) of induction motor (IM) drive is featured by high ripples in the electromagnetic torque and stator flux profiles because they are controlled by two…

Abstract

Purpose

The direct torque control (DTC) of induction motor (IM) drive is featured by high ripples in the electromagnetic torque and stator flux profiles because they are controlled by two hysteresis regulators. Furthermore, the machine flux is not directly measurable. Hence, it is better to reconstitute it from the instantaneous electrical equations of the machine. Once the stator flux is estimated, we can guarantee a reliable sensorless DTC control. Thus, the purpose of this research work is to ensure fast response and full reference tracking of the IM under sensorless DTC strategy with desired dynamic behavior and low ripple levels.

Design/methodology/approach

In this work, an improved DTC strategy, which is DTC_SVM_3L, is suggested. The first step of the designed approach is to substitute the conventional inverter feeding the motor with a three-level inverter because it guarantees reduced switching losses, improved quality of voltage waveform and low-current total harmonic distortion rate. The second aim of this paper is to make the IM operate at a constant switching frequency by using the nearest three vectors-based space vector modulation (SVM) technique rather than hysteresis controllers. The third objective of this study is to conceive a sliding-mode stator flux observer, which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The stability of the proposed observer is demonstrated based on the Lyapunov theory. To overcome the load change disturbance in the proposed DTC control strategy, this paper exhibits a comparative assessment of four speed regulation methods: classical proportional and integral (PI) regulator, fuzzy logic PI controller, particle swarm optimization PI controller and backstepping regulator. The entire control algorithm was tested under different disturbances such as stator resistance and load torque variations.

Findings

It was ascertained that the IM, controlled with three-level inverter, exhibits good performances under the proposed DTC-SVM strategy based on a sliding-mode observer. The robustness of the suggested approach against parameter variations is also proved.

Originality/value

The theoretical development of the proposed control strategy is thoroughly described. Then, simulations using Matlab/Simulink software are launched to investigate the merits of the sensorless DTC-SVM command of three-level inverter-fed IM drive with different speed regulators.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 31 January 2024

Ali Fazli and Mohammad Hosein Kazemi

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work…

Abstract

Purpose

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.

Design/methodology/approach

Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.

Findings

The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.

Practical implications

Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.

Originality/value

In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 12 September 2023

Shuwen Sun, Chenyu Song, Bo Wang and Haiming Huang

The safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight…

Abstract

Purpose

The safety performance of cooperative robots is particularly important. This paper aims to study collision detection and response of cooperative robots, which meet the lightweight requirements of cooperative robots and help to ensure the safety of humans and robots.

Design/methodology/approach

This paper proposes a collision detection, recognition and response method based on dynamic models. First, this paper identifies the dynamic model of the robot. Second, an external torque observer is established based on the model, and a dynamic threshold collision detection method is designed to reduce the interference of model uncertainty on collision detection. Finally, a collision position and direction estimation method is designed, and a robot collision response strategy is proposed to reduce the harm caused by collisions to humans.

Findings

Comparative experiments are conducted on static threshold and dynamic threshold collision detection, and the results showed that the static threshold only detected one collision while the dynamic threshold could detect all collisions. Conducting collision position and direction estimation and collision response experiments, and the results show that this method can determine the location and direction of collision occurrence, and enable the robot to achieve collision separation.

Originality/value

This paper designs a dynamic threshold collision detection method that does not require external sensors. Compared with static threshold collision detection methods, this method can significantly improve the sensitivity of collision detection. This paper also proposes a collision position direction estimation method and collision separation response strategy, which can enable robots to achieve post collision separation and improve the safety of cooperative robots.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 12 January 2024

Wei Xiao, Zhongtao Fu, Shixian Wang and Xubing Chen

Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this…

Abstract

Purpose

Because of the key role of joint torque in industrial robots (IRs) motion performance control and energy consumption calculation and efficiency optimization, the purpose of this paper is to propose a deep learning torque prediction method based on long short-term memory (LSTM) recurrent neural networks optimized by particle swarm optimization (PSO), which can accurately predict the the joint torque.

Design/methodology/approach

The proposed model optimized the LSTM with PSO algorithm to accurately predict the IRs joint torque. The authors design an excitation trajectory for ABB 1600–10/145 experimental robot and collect its relative dynamic data. The LSTM model was trained with the experimental data, and PSO was used to find optimal number of LSTM nodes and learning rate, then a torque prediction model is established based on PSO-LSTM deep learning method. The novel model is used to predict the robot’s six joint torque and the root mean error squares of the predicted data together with least squares (LS) method were comparably studied.

Findings

The predicted joint torque value by PSO-LSTM deep learning approach is highly overlapped with those from real experiment robot, and the error is quite small. The average square error between the predicted joint torque data and experiment data is 2.31 N.m smaller than that with the LS method. The accuracy of the novel PSO-LSTM learning method for joint torque prediction of IR is proved.

Originality/value

PSO and LSTM model are deeply integrated for the first time to predict the joint torque of IR and the prediction accuracy is verified.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 5 January 2024

Hongqiang Sang, Fang Huang, Wei Lu, Rui Han and Fen Liu

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio…

Abstract

Purpose

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio can increase inertia and decrease compliance of the manipulator. To enhance the backdrivability of the minimally invasive surgical robot, this paper aims to propose a resistance torque compensation algorithm.

Design/methodology/approach

A resistance torque compensation algorithm based on dynamics and Luenberger observer is proposed. The dynamics are established, considering joint flexibility and an improved Stribeck friction model. The dynamic parameters are experimentally identified by using the least squares method. With the advantages of clear structure, simple implementation and fast solution speed, the Luenberger observer is selected to estimate the unmeasured dynamic information of PSM and realize the resistance torque compensation.

Findings

For low-speed surgical robots, the centrifugal force term in the dynamic model can be simplified to reduce computational complexity. Joint flexibility and an improved Stribeck friction model can be considered to improve the accuracy of the dynamic model. Experiment results show that parameter identification and estimated results of the Luenberger observer are accurate. The backdrivability of the PSM is enhanced in ease and smoothness.

Originality/value

This algorithm provides potential application prospects for surgical robots to maintain high torque while remaining compliant. Meanwhile, the enhanced backdrivability of the manipulator helps to improve the safety of the preoperative manual adjustment.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 10 January 2024

Biqing Ye, Kebiao Zhang, Qiang Zuo, Li Zhang and Xiaohang Shan

The purpose of this paper is to test and analyze the friction torque of double-row angular contact ball bearings under vacuum or ordinary pressure environment, horizontal or…

54

Abstract

Purpose

The purpose of this paper is to test and analyze the friction torque of double-row angular contact ball bearings under vacuum or ordinary pressure environment, horizontal or upright installation mode, and different rotational speeds, and to provide theoretical bases for the development of aerospace equipment.

Design/methodology/approach

The experiments were carried out to investigate the effects of vacuum or ordinary pressure environment, horizontal or upright installation mode and different rotational speeds on bearing friction torque. To explore the relationship between working conditions and bearing friction torque, firstly, based on the generation source of friction torque, the test principle was determined, a test system was developed and the reliability of data was verified. Secondly, the friction torque of bearing was tested, and the values under various working conditions were obtained. Finally, this paper compared and discussed the test results.

Findings

The test results show that the friction torque value of vacuum environment horizontal installation condition is the largest at different rotational speeds, and the rotational speed has the most significant influence on the friction torque.

Originality/value

The friction torque test system of double-row angular contact ball bearing under vacuum environment was designed and built. The influence rules of vacuum or ordinary pressure environment, horizontal or upright installation mode and different rotational speeds on bearing friction torque were obtained.

Peer review

The peer review history for this article is available at: http://dx.doi.org/10.1108/ILT-08-2023-0259

Details

Industrial Lubrication and Tribology, vol. 76 no. 2
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 4 December 2023

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.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 10 July 2023

Jie Sun, X.F. Ge and Yuan Zheng

The research in this paper helps to understand the difference between the Eulerian method and the Lagrangian method in describing the performance of Pelton turbine buckets, so as…

Abstract

Purpose

The research in this paper helps to understand the difference between the Eulerian method and the Lagrangian method in describing the performance of Pelton turbine buckets, so as to improve the design level and design efficiency of the runner.

Design/methodology/approach

This paper used DualSPHysics to calculate the unsteady flow of the Pelton turbine runner bucket and compared it with the mesh-based method to explore the difference between mesh-based and particle-based methods in torque curves, jet flow patterns and pressure characteristics.

Findings

It is noted that the particle-based method is challenging to compare with the mesh-based method concerning accuracy. In addition to better describing the free water film, the particle method also captures many droplets near the water film, but it cannot well describe the negative pressure region on the bucket back and the resulting jet interference after cutting off the jet. Compared with the mesh-based method, the pressure measurement points obtained by the particle-based method generally have shorter periods and violent fluctuations, and the pressure value of some points is underestimated.

Originality/value

This paper helped to calculate the unsteady characteristics of the Pelton turbine by Fluent, CFX and DualSPHysics; exploration jet flow pattern differences between the mesh and meshfree methods; prediction of the flow interference between the bucket back and the jet and the pressure curve of SPH usually has a shorter period and violent fluctuations.

Details

Engineering Computations, vol. 40 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 6 June 2023

Yanli Feng, Ke Zhang, Haoyu Li and Jingyu Wang

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the…

150

Abstract

Purpose

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.

Design/methodology/approach

This paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.

Findings

Experiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.

Originality/value

The proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 11 January 2024

Yuepeng Zhang, Guangzhong Cao, Linglong Li and Dongfeng Diao

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in…

Abstract

Purpose

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

Design/methodology/approach

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Findings

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

Originality/value

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

Details

Robotic Intelligence and Automation, vol. 44 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

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