scholarly journals Design Sliding Mode Modified Fuzzy Linear Controller with Application to Flexible Robot Manipulator

2013 ◽  
Vol 5 (10) ◽  
pp. 53-63 ◽  
Author(s):  
Mahdi Mirshekaran ◽  
Farzin Piltan ◽  
Zahra Esmaeili ◽  
Tannaz Khajeaian ◽  
Meysam Kazeminasa
Keyword(s):  
Sliding Mode ◽  
Robot Manipulator ◽  
Flexible Robot ◽  
Linear Controller

scholarly journals Trajectory Tracking of a Flexible Robot Manipulator by a New Optimized Fuzzy Adaptive Sliding Mode-Based Feedback Linearization Controller

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
M. J. Mahmoodabadi ◽  
N. Nejadkourki
Keyword(s):  
Trajectory Tracking ◽  
Feedback Linearization ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Flexible Robot ◽  
Dynamical Equations ◽  
Control Effort ◽  
Adaptive Sliding Mode ◽  
Multiobjective Particle Swarm Optimization ◽  
Fuzzy Adaptive

This work presents a novel fuzzy adaptive sliding mode-based feedback linearization controller for trajectory tracking of a flexible robot manipulator. To reach this goal, after deriving the dynamical equations of the robot, the feedback linearization approach is utilized to change the nonlinear dynamics to a linear one and find the control law. Then, the sliding mode control strategy is implemented to design a stabilizer for trajectory tracking of the flexible robot. In order to adaptively tune the parameters of the designed controller, the gradient descent approach and the chain derivative rule are employed. Moreover, the Takagi–Sugeno–Kang fuzzy system is applied to regulate the controller gains. Finally, a multiobjective particle swarm optimization algorithm is used to find the optimum fuzzy rules. The conflicting objective functions considered as the integrals of the absolute values of the state error and the control effort should be minimized, simultaneously. The simulation results illustrate the effectiveness and capability of the introduced scenario in comparison with other methods.

scholarly journals Optimization of sliding mode control with PID surface for robot manipulator by Evolutionary Algorithms

2020 ◽  
Vol 10 (1) ◽  
pp. 396-407
Author(s):  
Fatiha Loucif ◽  
Sihem Kechida
Keyword(s):  
Sliding Mode ◽  
Robot Manipulator ◽  
Absolute Error ◽  
Grey Wolf Optimizer ◽  
Optimal Parameters ◽  
Error Criterion ◽  
Trajectory Tracking Control ◽  
Integral Time ◽  
Sine Cosine Algorithm ◽  
Antlion Optimization

AbstractIn this paper, a sliding mode controller (SMC) with PID surface is designed for the trajectory tracking control of a robot manipulator using different optimization algorithms such as, Antlion Optimization Algorithm (ALO) Sine Cosine Algorithm (SCA) Grey Wolf Optimizer (GWO) and Whale Optimizer Algorithm (WOA). The aim of this work is to introduce a novel SMC-PID-ALO to control nonlinear systems, especially the position of two of the joints of a 2DOF robot manipulator. The basic idea is to determinate four optimal parameters (Kp, Ki, Kd and lamda) ensuring the best performance of a robot manipulator system, minimizing the integral time absolute error criterion (ITAE) and the integral time square error criterion (ISTE). The robot manipulator is modeled in Simulink and the control is implemented using the MATLAB environment. The obtained simulation results prove the robustness of ALO in comparison with other algorithms.

scholarly journals Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3653
Author(s):  
Lilia Sidhom ◽  
Ines Chihi ◽  
Ernest Nlandu Kamavuako
Keyword(s):  
Degrees Of Freedom ◽  
Closed Loop ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Parametric Identification ◽  
Recursive Least Squares ◽  
Unknown Parameters ◽  
Closed Loop Identification ◽  
Input Variables ◽  
Robotic Applications

This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.

scholarly journals Compliant Human–Robot Collaboration with Accurate Path-Tracking Ability for a Robot Manipulator

2021 ◽  
Vol 11 (13) ◽  
pp. 5914
Author(s):  
Daniel Reyes-Uquillas ◽  
Tesheng Hsiao
Keyword(s):  
Sliding Mode ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Path Following ◽  
Path Tracking ◽  
Control Loop ◽  
Loop Control ◽  
Tracking Ability ◽  
The Difference ◽  
Human Robot Collaboration

In this article, we aim to achieve manual guidance of a robot manipulator to perform tasks that require strict path following and would benefit from collaboration with a human to guide the motion. The robot can be used as a tool to increase the accuracy of a human operator while remaining compliant with the human instructions. We propose a dual-loop control structure where the outer admittance control loop allows the robot to be compliant along a path considering the projection of the external force to the tangential-normal-binormal (TNB) frame associated with the path. The inner motion control loop is designed based on a modified sliding mode control (SMC) law. We evaluate the system behavior to forces applied from different directions to the end-effector of a 6-DOF industrial robot in a linear motion test. Next, a second test using a 3D path as a tracking task is conducted, where we specify three interaction types: free motion (FM), force-applied motion (FAM), and combined motion with virtual forces (CVF). Results show that the difference of root mean square error (RMSE) among the cases is less than 0.1 mm, which proves the feasibility of applying this method for various path-tracking applications in compliant human–robot collaboration.

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