Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator

Abstract

Arm robot manipulator is the most applied robot to substitute human labor in industries. Due to the importance of arm robot manipulator in manufacturing lines, the robustness and effective design are essential in building an arm robot. This paper presents the controller, mechanical, and motion designs of an arm robot manipulator. The fuzzy logic controller is employed to ensure the effectiveness in detecting the target object. PID controller is designed to enhance the smooth and stability of robot motion. The simulation of how the robot move inside its workspace was conducted using RSTX toolbox in SciLab. The motion is generated by deriving Denavit-Hartenberg parameters of the mechanical design. The result shows the effective design of Fuzzy-PID controller and mechanical design of a pick and places arm robot manipulator.

A Review of SCARA Robot Control System

“…As the PID controller is simple, PID controller is widely been used in many fields including robots application [24], [25]. However, the PID control only has good stability in a system that behaves linearly or near to linear [26].…”

“…Based on the digital operation of 1 and 0, the Fuzzy Logic Control is derived from mathematical logic to compute the signal between 1 and 0. The signal between 1 and 0 can be obtained from the input variable according to the membership function which was assigned as shown in Fig 2 and this process is called the inference engine [25]. As shown in Fig 2, the fuzzy logic will compute the signal according to the slope of the membership function.…”

Fuzzy Logic Controller Application for Automatic Charging System Design of a Solar Powered Mobile Manipulator

“…The battery's current capacity data is given by the amount of voltage collected from the solar cell. The feasibility of FLC design in this study is simulated using Scilab [23]- [27]. The number of membership function inputs shown in Figure 5 is from battery capacity and the amount of voltage produced by the solar panel.…”

“…The charging automation is supported by the Fuzzy Logic Controller (FLC) application to ensure the battery is never too low capacity or too full. Fuzzy Logic Controller (FLC) makes the robot decide based on the conditions found during its application [23]- [27]. Solar energy is promising because the robot is deployed in a field where the sunlight directly hits the PV panel and charges batteries [28].…”

Simulation Design of Artificial Intelligence Controlled Goods Transport Robot

“…In addition to sensors for input, robots require artificial intelligence (AI) to help them finish the assigned task. Fuzzy Logic Controller (FLC) [16]- [20] and Neural Network (NN) [21]- [26] are mainly used in AI.…”