Research

17 pages, 5103 KiB

Open AccessArticle

Research on Neural Network Terminal Sliding Mode Control of Robotic Arms Based on Novel Reaching Law and Improved Salp Swarm Algorithm

by Jianguo Duan, Hongzhi Zhang, Qinglei Zhang and Jiyun Qin

Actuators 2023, 12(12), 464; https://doi.org/10.3390/act12120464 - 13 Dec 2023

Viewed by 1115

Abstract

Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM), which combines fast nonsingular terminal sliding mode (FNTSM) [...] Read more.

Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM), which combines fast nonsingular terminal sliding mode (FNTSM) control, radial basis function (RBF) neural network, and an improved salp swarm algorithm (ALSSA). This method effectively enhances the trajectory tracking accuracy of robotic arms under the influence of uncertain factors. Firstly, the fast nonsingular terminal sliding surface is utilized to enhance the convergence speed of the system and achieve finite-time convergence. Building upon this, a novel multi-power reaching law is proposed to reduce system chattering. Secondly, the RBF neural network is utilized to estimate and compensate for modeling errors and external disturbances. Then, an improved salp swarm algorithm is proposed to optimize the parameters of the controller. Finally, the stability of the control system is demonstrated using the Lyapunov theorem. Simulation and experimental results demonstrate that the proposed ALSSA-RBFTSM algorithm exhibits superior robustness and trajectory tracking performance compared to the global fast terminal sliding mode (GFTSM) algorithm and the RBF neural network fast nonsingular terminal sliding mode (RBF-FNTSM) algorithm. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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17 pages, 5988 KiB

Open AccessArticle

High-Precision Control of Industrial Robot Manipulator Based on Extended Flexible Joint Model

by Siyong Xu, Zhong Wu and Tao Shen

Actuators 2023, 12(9), 357; https://doi.org/10.3390/act12090357 - 12 Sep 2023

Cited by 1 | Viewed by 1208

Abstract

High-precision industrial manipulators are essential components in advanced manufacturing. Model-based feedforward is the key to realizing the high-precision control of industrial robot manipulators. However, traditional feedforward control approaches are based on rigid models or flexible joint models which neglect the elasticities out of [...] Read more.

High-precision industrial manipulators are essential components in advanced manufacturing. Model-based feedforward is the key to realizing the high-precision control of industrial robot manipulators. However, traditional feedforward control approaches are based on rigid models or flexible joint models which neglect the elasticities out of the rotational directions and degrade the setpoint precision significantly. To eliminate the effects of elasticities in all directions, a high-precision setpoint feedforward control method is proposed based on the output redefinition of the extended flexible joint model (EFJM). First, the flexible industrial robots are modeled by the EFJM to describe the elasticities in joint rotational directions and out of the rotational directions. Second, the nonminimum-phase EFJM is transformed into a minimum-phase system by using output redefinition. Third, the setpoint control task is transformed from Cartesian space into joint space by trajectory planning based on the EFJM. Third, a universal recursive algorithm is designed to compute the feedforward torque based on the EFJM. Moreover, the computational performance is improved. By compensating the pose errors caused by elasticities in all directions, the proposed method can effectively improve the setpoint control precision. The effectiveness of the proposed method is illustrated by simulation and experimental studies. The experimental results show that the proposed method reduces position errors by more than 65% and the orientation errors by more than 62%. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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16 pages, 8365 KiB

Open AccessArticle

Design and Kinematic Characteristic Analysis of a Spiral Robot for Oil and Gas Pipeline Inspections

by Hongwei Yan, Pengyang Zhao, Canjun Xiao, Dengxiao Zhang, Shaoni Jiao, Haibing Pan and Xi Wu

Actuators 2023, 12(6), 240; https://doi.org/10.3390/act12060240 - 09 Jun 2023

Cited by 3 | Viewed by 1528

Abstract

This study presents a spiral pipeline robot designed for detecting and preventing oil and gas pipeline leakages. A comprehensive analysis of factors such as spiral angle, normal force, pipe material, and operating attitude is conducted based on the robot’s mechanical model in a [...] Read more.

This study presents a spiral pipeline robot designed for detecting and preventing oil and gas pipeline leakages. A comprehensive analysis of factors such as spiral angle, normal force, pipe material, and operating attitude is conducted based on the robot’s mechanical model in a straight pipe. This in-depth investigation determines the optimal spiral angle, normal force, pipeline material, and operating attitude to enhance the robot’s motion stability and traction performance. Using virtual prototype technology, the robot’s traction performance is simulated under various working conditions, normal forces, and attitude angles within the pipeline. An experimental platform is established to verify the impact of deflection angle, normal force, and pipeline material on traction performance. The experimental results and simulation analysis mutually validate each other, providing a reliable reference for robot design and optimization. The spiral pipeline robot and its motion strategy proposed in this study possess both theoretical value and practical application prospects in the field of oil and gas pipeline inspection and maintenance. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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20 pages, 11050 KiB

Open AccessArticle

Towards Metaverse: Utilizing Extended Reality and Digital Twins to Control Robotic Systems

by Tero Kaarlela, Tomi Pitkäaho, Sakari Pieskä, Paulo Padrão, Leonardo Bobadilla, Matti Tikanmäki, Timo Haavisto, Víctor Blanco Bataller, Niko Laivuori and Mika Luimula

Actuators 2023, 12(6), 219; https://doi.org/10.3390/act12060219 - 24 May 2023

Cited by 5 | Viewed by 2709

Abstract

Digitalization shapes the ways of learning, working, and entertainment. The Internet, which enables us to connect and socialize is evolving to become the metaverse, a post-reality universe, enabling virtual life parallel to reality. In addition to gaming and entertainment, industry and academia have [...] Read more.

Digitalization shapes the ways of learning, working, and entertainment. The Internet, which enables us to connect and socialize is evolving to become the metaverse, a post-reality universe, enabling virtual life parallel to reality. In addition to gaming and entertainment, industry and academia have noticed the metaverse’s benefits and possibilities. For industry, the metaverse is the enabler of the future digital workplace, and for academia, digital learning spaces enable realistic virtual training environments. A connection bridging the virtual world with physical production systems is required to enable digital workplaces and digital learning spaces. In this publication, extended reality–digital twin to real use cases are presented. The presented use cases utilize extended reality as high-level user interfaces and digital twins to create a bridge between virtual environments and robotic systems in industry, academia, and underwater exploration. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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18 pages, 8353 KiB

Open AccessArticle

Development of a Deformable Water-Mobile Robot

by Changlong Ye, Yang Su, Suyang Yu and Yinchao Wang

Actuators 2023, 12(5), 202; https://doi.org/10.3390/act12050202 - 12 May 2023

Cited by 2 | Viewed by 1230

Abstract

This article proposes a deformable water-mobile robot that can be used for rescue work. The robot body adopts an open-motion chain structure with two degrees of freedom, including two drive modules and one main control module. The three modules are connected through deformation [...] Read more.

This article proposes a deformable water-mobile robot that can be used for rescue work. The robot body adopts an open-motion chain structure with two degrees of freedom, including two drive modules and one main control module. The three modules are connected through deformation joints, and each drive module is equipped with an underwater thruster. The robot can obtain a triangle, linear shape, curved shape, and U-shape through deformation and have three types of motion: linear shape motion, U-shaped motion, and curved shape motion. In the linear shape, a multi-island genetic algorithm was used to optimize the structural parameters with the minimum resistance and the maximum volume. Floating state analysis was conducted in the U-shape, and the structural parameters were reasonably designed. By experimenting with the robot prototype on water, the robot can achieve oscillating, linear, U-shaped, and horizontal rotary motion, has an automatic adjustment function, and effective buoyancy meets the required requirements. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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17 pages, 4623 KiB

Open AccessArticle

Parallel Network-Based Sliding Mode Tracking Control for Robotic Manipulators with Uncertain Dynamics

by Honggang Wu, Xinming Zhang, Linsen Song, Yufei Zhang, Chen Wang, Xiaonan Zhao and Lidong Gu

Actuators 2023, 12(5), 187; https://doi.org/10.3390/act12050187 - 27 Apr 2023

Cited by 4 | Viewed by 1375

Abstract

Robot dynamics model uncertainty and unpredictable external perturbations are important factors that influence control accuracy and stability. To accurately compensate for the dynamics model in sliding mode control (SMC), a new parallel network (PCR) is proposed in this paper. The network parallelizes the [...] Read more.

Robot dynamics model uncertainty and unpredictable external perturbations are important factors that influence control accuracy and stability. To accurately compensate for the dynamics model in sliding mode control (SMC), a new parallel network (PCR) is proposed in this paper. The network parallelizes the radial basis function and convolutional neural network, which gives it the advantage of making full use of one-dimensional data fitting results and two-dimensional data feature information, realizing the deep learning of multidimensional data and improving the model’s compensation accuracy and anti-interference ability. Meanwhile, based on the integration of adaptive control techniques and gradient descent, a new weight update algorithm is designed to realize the online learning of PCR networks under loss-free functions. Then, a new sliding mode controller (PCR-SMC) is established. The model-free intelligent control of the robot is accomplished without knowledge of the predetermined upper bounds. Additionally, the stability analysis of the control system is proved by the Lyapunov theorem. Lastly, robot tracking control simulations are performed on two trajectories. The results demonstrate the high-precision tracking performance of this controller in comparison with the RBF-SMC controller. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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15 pages, 2331 KiB

Open AccessArticle

Design and Coverage Path Planning of a Disinfection Robot

by Pengjie Xu, Xinyi Chen and Qirong Tang

Actuators 2023, 12(5), 182; https://doi.org/10.3390/act12050182 - 24 Apr 2023

Cited by 1 | Viewed by 1702

Abstract

Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. [...] Read more.

Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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17 pages, 7208 KiB

Open AccessArticle

Electromechanical Coupling Dynamic and Vibration Control of Robotic Grinding System for Thin-Walled Workpiece

by Yufei Liu, Dong Tang and Jinyong Ju

Actuators 2023, 12(1), 37; https://doi.org/10.3390/act12010037 - 10 Jan 2023

Cited by 3 | Viewed by 1881

Abstract

The robotic grinding system for a thin-walled workpiece is a multi-dimensional coupling system composed of a robot, a grinding spindle and the thin-walled workpiece. In the grinding process, a dynamic coupling effect is generated, while the thin-walled workpiece stimulates elastic vibration; the grinding [...] Read more.

The robotic grinding system for a thin-walled workpiece is a multi-dimensional coupling system composed of a robot, a grinding spindle and the thin-walled workpiece. In the grinding process, a dynamic coupling effect is generated, while the thin-walled workpiece stimulates elastic vibration; the grinding spindle, as an electromechanical coupling actuator, is sensitive to the elastic vibration in the form of load fluctuations. It is necessary to investigate the electromechanical coupling dynamic characteristics under the vibration coupling of the thin-walled workpiece as well as the vibration control of the robotic grinding system. Firstly, considering the dynamic coupling effect between the grinding spindle and thin-walled workpiece, a dynamic model of the grinding spindle and thin-walled workpiece coupling system is established. Secondly, based on this established coupling dynamic model, the vibration characteristics of the thin-walled workpiece and the electromechanical coupling dynamic characteristics of the grinding spindle are investigated. Finally, a speed adaptive control system for the grinding spindle is designed based on a fuzzy PI controller, which can achieve a stable speed for the grinding spindle under vibration coupling and has a certain suppression effect on the elastic vibration of the thin-walled workpiece at the same time. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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13 pages, 3790 KiB

Open AccessArticle

Disturbance-Observer-Based Dual-Position Feedback Controller for Precision Control of an Industrial Robot Arm

by Namhyun Kim, Daejin Oh, Jun-Young Oh and Wonkyun Lee

Actuators 2022, 11(12), 375; https://doi.org/10.3390/act11120375 - 14 Dec 2022

Cited by 2 | Viewed by 2103

Abstract

Recently, the fourth industrial revolution has accelerated the application of multiple degrees-of-freedom (DOF) robot arms in various applications. However, it is difficult to utilize robot arms for precision motion control because of their low stiffness. External loads applied to robot arms induce deflections [...] Read more.

Recently, the fourth industrial revolution has accelerated the application of multiple degrees-of-freedom (DOF) robot arms in various applications. However, it is difficult to utilize robot arms for precision motion control because of their low stiffness. External loads applied to robot arms induce deflections in the joints and links, which deteriorates the positioning accuracy. To solve this problem, control methods using a disturbance observer (DOB) with an external sensory system have been developed. However, external sensors are expensive and have low reliability because of noise and reliance on the surrounding environment. A disturbance-observer-based dual-position feedback (DOB-DPF) controller is proposed herein to improve the positioning accuracy by compensating for the deflections in real time using only an internal sensor. The DOB was designed to derive the unpredictable disturbance torque applied to each joint using the command voltage generated by the position controller. The angular deflection of each joint was calculated based on the disturbance torque and joint stiffness, which were identified experimentally. The DPF controller was designed to control the joint motor while simultaneously compensating for angular deflection. A five-DOF robot arm testbed with a position controller was constructed to verify the proposed controller. The contouring performance of the DOB-DPF controller was compared with that of a conventional position controller with an external load applied to the end effector. The increases in the root mean square values of the contour errors were 1.71 and 0.12 mm with a conventional position controller and the proposed DOB-DPF controller, respectively, after a 2.2 kg weight was applied to the end effector. The results show that the contour error caused by the external load is effectively compensated for by the DOB-DPF controller without an external sensor. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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21 pages, 1690 KiB

Open AccessArticle

Adaptive Fault Tolerant Non-Singular Sliding Mode Control for Robotic Manipulators Based on Fixed-Time Control Law

by Saim Ahmed, Ahmad Taher Azar and Mohamed Tounsi

Actuators 2022, 11(12), 353; https://doi.org/10.3390/act11120353 - 29 Nov 2022

Cited by 14 | Viewed by 1910

Abstract

This paper presents a fault tolerant scheme employing adaptive non-singular fixed-time terminal sliding mode control (AFxNTSM) for the application of robotic manipulators under uncertainties, external disturbances, and actuator faults. To begin, non-singular fixed-time terminal sliding mode control (FxNTSM) is put forth. This control [...] Read more.

This paper presents a fault tolerant scheme employing adaptive non-singular fixed-time terminal sliding mode control (AFxNTSM) for the application of robotic manipulators under uncertainties, external disturbances, and actuator faults. To begin, non-singular fixed-time terminal sliding mode control (FxNTSM) is put forth. This control method uses non-singular terminal sliding mode control to quickly reach fixed-time convergence, accomplish satisfactory performance in tracking, and produce non-singular and non-chatter control inputs. Then, without knowing the upper bounds beforehand, AFxNTSM is used as a reliable fault tolerant control (FTC) to estimate actuator faults and unknown dynamics. The fixed-time stability of the closed-loop system is established by the theory of Lyapunov analysis. The computer simulation results of the position tracking, control inputs, and adaptive parameters are presented to verify and illustrate the performance of the proposed strategy. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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18 pages, 5686 KiB

Open AccessArticle

Robust Stabilization of Underactuated Two-Wheeled Balancing Vehicles on Uncertain Terrains with Nonlinear-Model-Based Disturbance Compensation

by Yongkuk Kim and SangJoo Kwon

Actuators 2022, 11(11), 339; https://doi.org/10.3390/act11110339 - 21 Nov 2022

Cited by 4 | Viewed by 2127

Abstract

Two-wheeled inverted pendulum (TWIP) vehicles are prone to lose their mobility and postural stability owing to their inherently unstable and underactuated dynamic characteristics, specifically when they encounter abruptly changed slopes or ground friction. Overcoming such environmental disturbances is essential to realize an agile [...] Read more.

Two-wheeled inverted pendulum (TWIP) vehicles are prone to lose their mobility and postural stability owing to their inherently unstable and underactuated dynamic characteristics, specifically when they encounter abruptly changed slopes or ground friction. Overcoming such environmental disturbances is essential to realize an agile TWIP-based mobile platform. In this paper, we suggest a disturbance compensation method that is compatible with unmanned TWIP systems in terms of the nonlinear-model-based disturbance observer, where the underactuated dynamic model is transformed to a fully actuated form by regarding the gravitational moment of the inverted pendulum as a supplementary pseudo-actuator to counteract the pitch-directional disturbances. Consequently, it enables us to intuitively determine the disturbance compensation input of the two wheels and the pitch reference input accommodating to uncertain terrains in real time. Through simulation and experimental results, the effectiveness of the proposed method is validated. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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24 pages, 7546 KiB

Open AccessArticle

Time-Optimal Trajectory Planning of 6-DOF Manipulator Based on Fuzzy Control

by Feifan He and Qingjiu Huang

Actuators 2022, 11(11), 332; https://doi.org/10.3390/act11110332 - 16 Nov 2022

Cited by 5 | Viewed by 1772

Abstract

Currently, the teaching programming or offline programming used by an industrial manipulator can manually set the running speed of the manipulator. In this paper, to consider the running speed and stability of the manipulator, the time-optimal trajectory planning (TOTP) of the manipulator is [...] Read more.

Currently, the teaching programming or offline programming used by an industrial manipulator can manually set the running speed of the manipulator. In this paper, to consider the running speed and stability of the manipulator, the time-optimal trajectory planning (TOTP) of the manipulator is transformed into a nonlinear optimal value search problem under multiple constraints, and a time-search algorithm based on fuzzy control is proposed, so that the end of the manipulator can run along the given path in Cartesian space for the shortest time, and the angular velocity and angular acceleration of each joint is within a limited range. In addition, a simulation model of a 6-DOF manipulator is established in MATLAB, taking a straight-line trajectory of the end of the manipulator in Cartesian space as an example, and the effectiveness and efficiency of the algorithm proposed in this paper are proved by comparing the execution time with the bisection algorithm and the traditional gradient descent method. Full article

(This article belongs to the Special Issue Modeling, Optimization and Control of Robotic Systems)

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