scholarly journals Modelling an Industrial Robot and Its Impact on Productivity

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 769
Author(s):  
Carlos Llopis-Albert ◽  
Francisco Rubio ◽  
Francisco Valero
Keyword(s):  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Industrial Robot ◽  
System Stability ◽  
Optimal Time ◽  
Tracking Accuracy ◽  
Six Degrees Of Freedom ◽  
Trade Offs ◽  
Fuzzy Sliding Mode ◽  
Pareto Fronts

This research aims to design an efficient algorithm leading to an improvement of productivity by posing a multi-objective optimization, in which both the time consumed to carry out scheduled tasks and the associated costs of the autonomous industrial system are minimized. The algorithm proposed models the kinematics and dynamics of the industrial robot, provides collision-free trajectories, allows to constrain the energy consumed and meets the physical characteristics of the robot (i.e., restriction on torque, jerks and power in all driving motors). Additionally, the trajectory tracking accuracy is improved using an adaptive fuzzy sliding mode control (AFSMC), which allows compensating for parametric uncertainties, bounded external disturbances and constraint uncertainties. Therefore, the system stability and robustness are enhanced; thus, overcoming some of the limitations of the traditional proportional-integral-derivative (PID) controllers. The trade-offs among the economic issues related to the assembly line and the optimal time trajectory of the desired motion are analyzed using Pareto fronts. The technique is tested in different examples for a six-degrees-of-freedom (DOF) robot system. Results have proved how the use of this methodology enhances the performance and reliability of assembly lines.

Application of non-linear H∞ control to the Tetrabot robot manipulator

1998 ◽  
Vol 212 (6) ◽  
pp. 459-465 ◽  
Author(s):  
I Postlethwaite ◽  
A Bartoszewicz
Keyword(s):  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
External Disturbances ◽  
Six Degrees Of Freedom ◽  
Control Scheme ◽  
Non Linear ◽  
Modelling Uncertainties ◽  
Real Robot ◽  
Robotic Application

In this paper, an application of a non-linear H∞ control law for an industrial robot manipulator is presented. Control of the manipulator motion is formulated into a non-linear H∞ optimization problem, namely optimal tracking performance in the presence of modelling uncertainties and external disturbances. Analytical solutions for this problem are implemented on a real robot. The robot under consideration is the six-degrees-of-freedom GEC Tetrabot. Investigations are made into the selection of weights for the H∞ controller and it is shown how different selections of weights affect the Tetrabot performance. The authors believe this to be the first robotic application of nonlinear H∞ control. Comparisons of the proposed control strategy with conventional proportional-derivative and proportional-integral-derivative controllers show favourable performance of the Tetrabot under the new non-linear H∞ control scheme.

Heading control of a novel finless high-speed supercavitating vehicle with an internal oscillating pendulum

2020 ◽  
pp. 107754632094834
Author(s):  
Mojtaba Mirzaei ◽  
Hossein Taghvaei
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Six Degrees Of Freedom ◽  
Supercavitating Vehicles ◽  
Supercavitating Vehicle ◽  
High Speeds ◽  
Heading Control ◽  
Heading Angle ◽  
Control Surfaces

High-speed supercavitating vehicles are surrounded by a huge cavity of gas and only a small portion of the nose and the tail of the vehicle are in contact with the water which leads to a considerable reduction in skin friction drag and reaching very high speeds. High-speed supercavitating vehicles are usually controlled by the cavitator at the nose which controls the pitch and depth of the vehicle and the control surfaces or fins which control the roll and heading angle of the vehicle using the bank-to-turn maneuvering method. However, control surfaces have disadvantages such as the high drag force and ineffectiveness due to the supercavity. Therefore, the purpose of the present study is to eliminate the fins from high-speed supercavitating vehicles and propose a new bank-to-turn heading control of this novel finless high-speed supercavitating vehicle which is composed of the cavitator at the nose and an oscillating pendulum as the internal actuator. Sliding mode control as a robust method is used for the six-degrees-of-freedom model of this finless high-speed vehicle against exposed disturbances. Some design criteria for the design of the internal pendulum in this finless supercavitating vehicle are presented for the damping coefficient, pendulum mass, and radius.

scholarly journals Crack Assessment of Wheel Hubs via an Ultrasonic Transducer and Industrial Robot

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4336 ◽  
Author(s):  
Hanming Zhang ◽  
Chunguang Xu ◽  
Dingguo Xiao
Keyword(s):  
Crack Growth ◽  
Ultrasonic Testing ◽  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Ultrasonic Transducer ◽  
Robot Assisted ◽  
Six Degrees Of Freedom ◽  
Crack Location ◽  
Critical Areas ◽  
Growth Assessment

Crack assessment when making fitness-for-service decisions requires a thorough examination of crack location and size in critical areas. An ultrasonic transducer is used for such assessments, but traditional methods cannot cope with complex rotators, such as wheel hubs. We present a model of robot-assisted crack growth assessment in wheel hubs. We integrate a six-degrees-of-freedom (DOF) industrial robot and a turntable to form a robot-assisted ultrasonic testing (UT) system that does not use traditional UT equipment. Ultrasonic beams are focused at certain depths appropriate for achieving maximum sensitivity. We quantitatively analysed wheel hubs with longitudinal and transverse series of pre-cracks, and concluded that our system autonomously detected cracks.

Fuzzy Sliding Mode Control of Robotic Manipulators With Kinematic and Dynamic Uncertainties

2012 ◽  
Vol 134 (6) ◽  
Author(s):  
Haitao Liu ◽  
Tie Zhang
Keyword(s):  
Fuzzy Logic ◽  
Sliding Mode Control ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Robotic Manipulator ◽  
Mode Control ◽  
Control Scheme ◽  
Adaptive Fuzzy Logic ◽  
Fuzzy Sliding Mode ◽  
Dynamic Uncertainties

Sliding mode control is a very attractive control scheme with strong robustness to structured and unstructured uncertainties as well as to external disturbances. In this paper, a robust fuzzy sliding mode controller, which is combined with an adaptive fuzzy logic system, is proposed to improve the control performance of the robotic manipulator with kinematic and dynamic uncertainties. In this controller, the sliding mode control is employed to improve the control accuracy and the robustness of the robotic manipulator, and the fuzzy logic control is adopted to approximate various uncertainties and to eliminate the chattering without the help of any prior knowledge of system uncertainties. The effectiveness of the proposed controller is then verified by the simulations on a 2-DOF (degrees of freedom) robotic manipulator and the experiments on an SCARA robot with four degrees of freedom. Simulated and experimental results indicate that the proposed controller is effective in the robust tracking of the robotic manipulator with kinematic and dynamic uncertainties.

Precision Control of a Piezo-Actuate System Using Fuzzy Sliding-Mode Control with Feedforward Predictor-Based Compensation

2008 ◽  
Vol 594 ◽  
pp. 401-406 ◽  
Author(s):  
Jin Wei Liang ◽  
Hung Yi Chen ◽  
Shy Yaw Chiang
Keyword(s):  
Sliding Mode Control ◽  
Piezoelectric Actuator ◽  
Sliding Mode ◽  
Tracking Error ◽  
Tracking Accuracy ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Control Schemes ◽  
Fuzzy Sliding Mode ◽  
Hysteretic Characteristics

The fuzzy sliding-mode control strategy is used to tackle tracking problem of a piezo-actuated stage in this paper. The piezo-actuated system is composed of the piezoelectric actuator and a positioning mechanism. Due to hysteretic nonlinearity of the piezoelectric actuator, the tracking accuracy of the system is limited. To compensate for this nonlinearity, a feedback fuzzy sliding-mode control augmented with a predictor-based feedforward compensator is proposed. The controller, denoted as the feedforward-feedback fuzzy sliding-mode controller (FF-FSMC), can be applied to eliminate tracking error caused by the hysteretic characteristics. Experimental results on different types of reference inputs indicate that the proposed control schemes may suppress the tracking error of the piezo-actuated system effectively.

scholarly journals ABB IRB 120-30.6 Build Procedure in RoboDK

2021 ◽  
pp. 256-264
Author(s):  
Sudip Chakraborty ◽  
P. S. Aithal
Keyword(s):  
Design Methodology ◽  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Research Purpose ◽  
Six Degrees Of Freedom ◽  
Simulation Based ◽  
Software Download ◽  
Coordinate Assignment

Purpose: Research on robotics needs a robot to experiment on it. The actual industrial robot is costly. So, the only resort is to use a Robot simulator. The RoboDK is one of the best robot simulators now. It has covered most of the popular industrial robots. Its interface is straightforward. Just open the software, download the robot as we need, and start experiments. Up to that, no issue was found anywhere. However, the problem begins when we want to build the simulated robot by own. Lots of complexity arises like coordinate assignment, rotation not aligned, length mismatch, robot not synced with DH parameter. We begin to find some documents for making the robots. A few bits of the document are present. That is why we research it. After doing that, we prepared this paper for the researcher who wants to develop the simulated robot independently. This paper can be referenced for them. To minimize the complexity of our research, we study an industrial robot, ABB IRB 120-30.6. It is a good and popular robot. It is six degrees of freedom robot. We will use the specification and STEP file from their respective website and build a simulated robot from the STEP file for our research purpose. Design/Methodology/Approach: We will create a simulated robot from ABB IRB 120-30.6 STEP file. To create a robot by own, we took the help of the IRB 120 robot model. To demonstrate as simple as possible, we start with that robot whose default design is already present. We match and tune the joint coordinate based on robot parameters through this experiment. Findings/results: Here, we see how to create a custom robot. Using the IRB 120 robot model, we will create a robot model step by step. Furthermore, it will move it around its axis. Originality/Value: Using this experiment, the new researcher can get valuable information to create their custom robot. Paper Type: Simulation-based Research.

scholarly journals Output Error Methods for Robot Identification

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Mathieu Brunot ◽  
Alexandre Janot ◽  
Francisco Carrillo ◽  
Joono Cheong ◽  
Jean-Philippe Noël
Keyword(s):  
Degrees Of Freedom ◽  
Target Identification ◽  
Industrial Robot ◽  
Computational Time ◽  
Dynamic Identification ◽  
Inverse Dynamic ◽  
Six Degrees Of Freedom ◽  
Output Error ◽  
Modeling Errors ◽  
Regression Techniques

Abstract Industrial robot identification is usually based on the inverse dynamic identification model (IDIM) that comes from Newton's laws and has the advantage of being linear with respect to the parameters. Building the IDIM from the measurement signals allows the use of linear regression techniques like the least-squares (LS) or the instrumental variable (IV) for instance. Nonetheless, this involves a careful preprocessing to deal with sensor noise. An alternative in system identification is to consider an output error approach where the model's parameters are iteratively tuned in order to match the simulated model's output and the measured system's output. This paper proposes an extensive comparison of three different output error approaches in the context of robot identification. One of the main outcomes of this work is to show that choosing the input torque as target identification signal instead of the output position may lead to a gain in robustness versus modeling errors and noise and in computational time. Theoretical developments are illustrated on a six degrees-of-freedom rigid robot.

scholarly journals Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension

2021 ◽  
Vol 11 (22) ◽  
pp. 10925
Author(s):  
Gang Li ◽  
Zhiyong Ruan ◽  
Ruiheng Gu ◽  
Guoliang Hu
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Mr Damper ◽  
Suspension System ◽  
System Stability ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Air Suspension ◽  
Road Excitation ◽  
Fuzzy Sliding Mode

In order to reduce vehicle vibration during driving conditions, a fuzzy sliding mode control strategy (FSMC) for semi-active air suspension based on the magnetorheological (MR) damper is proposed. The MR damper used in the semi-active air suspension system was tested and analyzed. Based on the experimental data, the genetic algorithm was used to identify the parameters of the improved hyperbolic tangent model, which was derived for the MR damper. At the same time, an adaptive neuro fuzzy inference system (ANFIS) was used to build the reverse model of the MR damper. The model of a quarter vehicle semi-active air suspension system equipped with a MR damper was established. Aiming at the uncertainty of the air suspension system, fuzzy control was used to adjust the boundary layer of the sliding mode control, which can effectively suppress the influence of chattering on the control accuracy and ensure system stability. Taking random road excitation and impact road excitation as the input signal, the simulation analysis of passive air suspension, semi-active air suspension based on SMC and FSMC was carried out, respectively. The results show that the semi-active air suspension based on FSMC has better vibration attenuating performance and ride comfort.

scholarly journals MIMO Fuzzy Sliding Mode Control for Three-Axis Inertially Stabilized Platform

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1658 ◽  
Author(s):  
Zhanmin Zhou ◽  
Bao Zhang ◽  
Dapeng Mao
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Stability And Convergence ◽  
Tracking Accuracy ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Fuzzy Sliding Mode ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

In this paper, a MIMO (Multi-Input Multi-Output) fuzzy sliding mode control method is proposed for a three-axis inertially stabilized platform. This method is based on the MIMO coupling model of the three-axis inertially stabilized platform in which the dynamic coupling among the three frames, namely the azimuth frame, the pitch frame and the roll frame, is fully considered. Firstly, the dynamic equation of the three-axis inertially stabilized platform is analyzed and its linearized model is obtained. After this, the controller is designed based on the model, during which fuzzy logic is introduced to deal with the frame coupling and the adaptive fuzzy coupling compensation factor is designed to be part of the algorithm. A complete proof of the stability and convergence is also provided in this paper. Finally, the performance of the platform with a MIMO fuzzy sliding mode controller and PI controller is analyzed. The simulation results show that the proposed scheme can guarantee tracking accuracy and effectively suppress the coupling interference between the three frames.

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