Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm Optimization

Mahmoodabadi, Mohammad Javad; Ziaei, Amin

doi:10.1155/2019/5052185

Cited by 22 publications

(5 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The constrains is included in the singularities block implies the difference between the real tuple position and the reference tuple should not exceed 0.6. The Homogeneous Transformation Matrix is obtained according to [23,24] is shown in (11).…”

Section: Kinenamatic Robotmentioning

confidence: 99%

Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

et al. 2021

View full text Add to dashboard Cite

The robots pay important role in all parts of our life. Hence, the modeling of the robot is essential to develop the performance specification. Robot model of six degree of freedom (6DoF) manipulator implemented numerically using model-based technique. The kinematic analysis and simulation were studied with Inverse kinematics of the robot manipulator through Denevit and Hartenberg method. Matrix transformation method is used in this work in order to separate joint variables from kinematic equations. The finding of the desired configuration is obtained precisely in all motion trajectory along the end-effector path. MATLAB/SIMULINK with R2018b is used for the implementation of the model-based robot system. Simulation results showed that the robot rinks follow their references smoothly and precisely and ensure the effectiveness of direct kinematic algorithm in the analysis and control of the robotic field.

show abstract

Section: Kinenamatic Robotmentioning

confidence: 99%

Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

et al. 2021

View full text Add to dashboard Cite

show abstract

“…When the right foot is moving, the transformation matrix will proceed from the world coordinate frame to the left foot and vice-versa. Mahmoodabadi & Ziaei (2019) proposed a DH approach and Jacobi method for each of the arms of a robot in order to gain the kinematic equations of the manipulator. Furthermore, the Lagrange method was utilized to obtain the dynamic equations of motion.…”

Section: Related Workmentioning

confidence: 99%

Development of forward kinematics and construction of the driving and command system of a robotic manipulator

Mendes

Oliveira

2020

jme

View full text Add to dashboard Cite

The idea of working with a robotic manipulator came from the availability of doing a retrofit of the drive and command system for the RD5 robot, a manipulator that is part of the IFCE's Energy Processing Laboratory. The challenges of working with this robot is the fact this manipulator has not been used for some time, needing adjustments such as tightening its joints, redo connections and add potentiometers instead of damaged ones. The objectives of this work are the development of forward kinematics (FK) and the construction of its drive and command system. The expected positions are obtained from FK using the Denavit-Hatenberg (DH) method. The expected positioning of the manipulator in each situation was compared with that obtained through the drive and command system and thus it was possible to perform the acquisition of position error estimation data. The results were then discussed.

show abstract

“…Nevertheless, the effectiveness of FLC can be improved if the dynamic modeling is incorporated. For example, in [7], inverse dynamics were used in a fuzzy-model-based adaptive robust controller for the tracking control of a parallel manipulator and for reducing the chattering, and in [8], a dynamics-based optimal fuzzy controller for a robot manipulator via particle swarm optimization was inspected. It was found that the fuzzy controller based on inverse dynamics provides a near-zero steady state error.…”

Section: Introductionmentioning

confidence: 99%

Design, Simulation, Implementation, and Comparison of Advanced Control Strategies Applied to a 6-DoF Planar Robot

Urrea

Saa

2023

Symmetry

View full text Add to dashboard Cite

In general, structures with rotational joints and linearized dynamic equations are used to facilitate the control of manipulator robots. However, in some cases, the workspace is limited, which reduces the accuracy and performance of this type of robot, especially when uncertainties are considered. To counter this problem, this work presents a redundant planar manipulator robot with Six-Degree-of-Freedom (6-DoF), which has an innovative structural configuration that includes rotary and prismatic joints. Three control strategies are designed for the monitoring and regulation of the joint trajectory tracking problem of this robot under the action of variable loads. Two advanced control strategies—predictive and Fuzzy-Logic Control (FLC)—were simulated and compared with the classical Proportional–Integral–Derivative (PID) controller. The graphic simulator was implemented using tools from the MATLAB/Simulink software to model the behavior of the redundant planar manipulator in a virtual environment before its physical construction, in order to conduct performance tests for its controllers and to anticipate possible damages/faults in the system mechanics before the implementation of control strategies in a real robot. The inverse dynamics were obtained through the Lagrange–Euler (L-E) formulation. According to the property of symmetry, this model was obtained in a simplified way based on the main diagonal of the inertia matrix of the robot. Additionally, the model includes the dynamics of the actuators and the estimation of the friction forces, both with central symmetry present in the joints. The effectiveness of these three control strategies was validated through qualitative comparisons—performance graphs of trajectory tracking—and quantitative comparisons—the Common Mode Rejection Ratio (CMRR) performance indicator and joint error indexes such as the Residual Mean Square (RMS), Residual Standard Deviation (RSD), and Index of Agreement (IA). In this regard, FLC based on the dynamic model was the most-suitable control strategy.

show abstract

Inverse Dynamics Based Optimal Fuzzy Controller for a Robot Manipulator via Particle Swarm Optimization

Cited by 22 publications

References 63 publications

Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

Robot control and kinematic analysis with 6DoF manipulator using direct kinematic method

Development of forward kinematics and construction of the driving and command system of a robotic manipulator

Design, Simulation, Implementation, and Comparison of Advanced Control Strategies Applied to a 6-DoF Planar Robot

Contact Info

Product

Resources

About