Intelligent control of four DOF robotic arm

Nagpal, Neelu; Bhushan, Bharat; Agarwal, Vijyant

doi:10.1109/icpeices.2016.7853357

Cited by 4 publications

(1 citation statement)

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“…Optimization can help with the resolution of kinematics problems and contribute to robotics. Another area of fuzzy logic research is the use of fuzzy control and adaptive network fuzzy interference system approaches to regulate the joint position of a 4-DOF robotic arm to achieve the desired movement [13]. Furthermore, the system's performance is compared to that of a traditional PID controller in terms of overshoot, settling time, and steady-state inaccuracy in this study.…”

Section: Mamdani Fuzzy Interference System (Fis)mentioning

confidence: 99%

Robotic Arm Position Control using Mamdani Fuzzy Logic on Arduino Microcontroller

Hamzah¹,

Thamrin²,

Tajjudin³

2022

JMechE

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A robotic arm is the most often used robot in manufacturing to perform the same task accurately again and over again in a controlled environment. However, direct positioning control of the robotic arm is always inaccurate as it does not consider its position in the external environment. Therefore, this work implements the Mamdani fuzzy logic in the position control of the 6 DOF robotic arm to improve the accuracy and movement of each joint at this manipulator. The implemented fuzzy logic Mamdani inference system is done in MATLAB and finally converted to the C language to accommodate the main microcontroller, Arduino UNO environment. There are 6 servo motors controlled by this approach and the result is compared with the conventional method. It is found that the Mamdani fuzzy logic controller has an average error of 0.67% while the direct control method has an average error of 2.33%. Based on this result, it shows that the use of the Mamdani fuzzy logic increases the accuracy and reduces the swaying movement after stopping the robotic arm movement.

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Section: Mamdani Fuzzy Interference System (Fis)mentioning

confidence: 99%