An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

Elawady, Wael M.; Bouteraa, Yassine; Elmogy, Ahmed M.

doi:10.3390/robotics9010004

Cited by 3 publications

(1 citation statement)

References 41 publications

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“…The results showed the first network errors are very minimal compared to other networks. Furthermore, an advanced logics is proposed to solve the inverse of robot manipulator like adaptive fuzzy self-tuning control system [10]. An artificial neural fuzzy inference system (ANFIS) was based to analyze the kinematics of 4-DOFs SCARA robot in order to utilize for desired path generation [11].…”

Section: Introductionmentioning

confidence: 99%

Arduino-based implementation of kinematics for a 4 DOF robot manipulator using artificial neural network

Rashid,

Sarhan,

Hassan

2024

Diagnostyka

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Real-time motion control is basically dependent on robot kinematics analysis where there is no unique solution of the inverse kinematics of serial manipulators. The predictive artificial neural network is a powerful one for finding appropriate results based on training data. Therefore, an artificial neural network is proposed to implement on Arduino microcontroller for a 4-DOF robot manipulator where the inverse kinematics problem was partitioned to suit the low specification of the board CPU. With MATALB toolbox, multiple neural network configuration based were trained and experienced for the best fit of the dimensionless feedforward data that is obtained from the forward kinematics of reachable workspace with average MSE of 6.5e-7. The results showed the superior of the proposed networks reducing the joints error by 90 % at least with comparing to traditional one. An Arduino on-board program was developed to control the robot independly based on pre validated parameters of the network. The experimental results approved the proposed method to implement the robot in real time with maximum error of (± 0.15 mm) in end effector position. The presented approach can be applied to achieve a suitable solution of n-DOF self-depend robot implementation using micro stepping actuators.

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Section: Introductionmentioning

confidence: 99%

Arduino-based implementation of kinematics for a 4 DOF robot manipulator using artificial neural network

Rashid,

Sarhan,

Hassan

2024

Diagnostyka

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Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator

Rezoug

Iqbal

Tadjine

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article proposes a novel hybrid metaheuristic technique based on nonsingular terminal sliding mode controller, time delay estimation method, an extended grey wolf optimization algorithm and adaptive super twisting control law. The fast convergence is assured by nonsingular terminal sliding mode controller owing to its inherent nonlinear property and no prior knowledge of the robot dynamics is required due to time delay estimation. The proposed extended grey wolf optimization algorithm determines an optimal approximation of the inertial matrix of the robot. Moreover, adaptive super twisting control based on the Lyapunov approach overcomes the disturbances and compensate the higher dynamics not achievable by the time delay estimation method. First, the fast nonsingular terminal sliding mode controller relying on time delay estimation is designed and is combined with super twisting control for chattering attenuation. The constant gain matrix of the time delay is determined by the proposed extended grey wolf optimization algorithm. Second, an adaptive law based on Lyapunov stability theorem is designed for improving tracking performance in the presence of uncertainties and disturbances. The novelty of the proposed method lies in the adaptive law where the prior knowledge of parametric uncertainties and disturbances is not needed. Moreover, the constant gain matrix of time delay estimation method is obtained using the proposed algorithm. The control method has been tested in simulation on a 3-degrees of freedom robotic manipulator in trajectory tracking mode in the presence of control disturbances and uncertainties. The results obtained confirmed the effectiveness, robustness and the superior precision of the proposed control method compared to the classical ones.

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Adaptive Sliding Mode Control Anticipating Proportional Degradation of Actuator Torque in Uncertain Serial Industrial Robots

Truc

Thoan

et al. 2022

Symmetry

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The paper focuses on faulty actuator problems in an industrial robot using servomotors, and provides an adaptive sliding mode control law to overcome this circumstance. Because of multifarious reasons, robot actuators can undergo a variety of failures, such as locked or stuck joints, free-swinging joints, and partial or total loss of actuation effectiveness. The robot behavior will become worsen if the system controller has not been designed with adequate faulty tolerance. The proportional degradation of actuator torque at unknown degrees of loss, which is one type of partial loss of actuation effectiveness, is considered in this study to design a suitable controller. The robot model is constructed with uncertain parameters and unknown friction, whereas the controller uses only the approximate parameters. Symmetry and skew-symmetry give important contributions in robot modeling and transformation, as well as in the process of proving the system stability. An adjustable coefficient vector of the proposed controller can adaptively reach the upper bounds of an uncertain parametric vector, which guarantees the criterion of Lyapunov stability. In the numerical simulation stage, the selected industrial robot is a Serpent 1 robot with three degrees of freedom. A quasi-physical model based on MATLAB/Simscape Multibody for the robot is built and used in order to increase the reliability of the simulation performance closer to reality. Simulation results illustrate the efficiency of the proposal control methodology in the presence of the mentioned failure. The controller can still deliver satisfactory responses to the robot system under reasonable levels of actuator torque degradation.

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An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

Cited by 3 publications

References 41 publications

Arduino-based implementation of kinematics for a 4 DOF robot manipulator using artificial neural network

Arduino-based implementation of kinematics for a 4 DOF robot manipulator using artificial neural network

Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator

Adaptive Sliding Mode Control Anticipating Proportional Degradation of Actuator Torque in Uncertain Serial Industrial Robots

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