Hybrid ANFIS Controller for 6-DOF Manipulator with 3D Model

Yousif Al Mashhadany

doi:10.24297/ijct.v4i2c2.4188

Abstract

This paper proposes a hybrid ANFIS (Adaptive Neuro-Fuzzy Inference System) controller with DMRAC (Direct Model Reference Adaptive Control) and mathematical modeling of the kinematic and dynamic solutions. The controller was hybrid with a classical controller, and was designed for a spherical-wristed 6-DOF elbow manipulator. The manipulatorâ€™s trajectory overshoot and settling time affect movement; their minimization was thus aimed for. The whole manipulator-controller system was modeled and simulated on MATLAB Version 2011a and Robotics Toolbox 9. To increase accuracy, the ANFIS controller was trained to use many paths in rules and memberships selection. A 3D display model for the manipulator was built in MATLAB. The simulation of the design had done by using the MATLAB/SIMULINK through connection the design with 3D model. Satisfactory results show the hybrid controllerâ€™s capacity for precision and speed, both of which are higher than a classical controllerâ€™s alone.

Highlights

Intelligent control systems increase the effectiveness of control strategies and overcome limits of classical and adaptive controllers
This paper proposes a hybrid Direct Model Reference Adaptive Control (DMRAC)-based ANFIS-classical controller for a spherical-wristed 6-DOF manipulator
The proposed design was simulated by VR modeling on MATLAB Version 2011a with Robotics Toolbox 9

Summary

Introduction

Intelligent control systems increase the effectiveness of control strategies and overcome limits of classical and adaptive controllers. Hybrid ANFIS controller, 6-DOF Manipulator, Direct Model Reference Adaptive Control (DMRAC) Basic to neuro-adaptive learning techniques is a fuzzy modeling procedure that learns the data set and automatically computes the membership function parameters that best allow the associated FIS to track the given input/output data [6,7].

Results

Conclusion