ANFIS PD+I Based Hybrid Force/ Position Control of an Industrial Robot Manipulator

Abstract

Abstract-A hybrid force plus position controller based on adaptive neuro fuzzy inference system proportional derivative + integral (ANFIS-PD+I), with unspecified robot dynamics has been proposed for a robot manipulator under constrained environment. The proposed controller has been employed as a principal controller to tune up orthodox PID gains throughout the complete trajectory tracking process. The validity of the proposed controller has been studied using a 6-Degree of Freedom (DOF) PUMA robot manipulator. Simulation outcomes illustrates that the projected force / position controller adheres to the desired path closer and smoother.Index Terms-Adaptive neuro fuzzy control, degrees of freedom, force control, position control, robot manipulator.

Optimal Design and Performance Comparison of a Combined ANFIS-PID with Back Stepping Technique, Using Various Meta-Heuristic Algorithms to Solve Wheeled Mobile Robot Trajectory Tracking Problem

“…The ANFIS could solve this problem by combining fuzzy logic controller advantage to deal with the uncertainties with the ability of neural networks to learn from plants/processes, this concept has attracted an exceptional attention in various engineering fields [36][37][38][39][40]. In this context, several hybrid designs have been made to enhance the robustness of the ANFIS controlled system, by benefiting from advantage and simplicity of a PID controller, we distingue the following mergers: hybrid ANFIS-PID [41][42][43], (ANFIS+I) controller optimizing using multidimensional PSO for Quadrotor Position Control [44], (ANFIS-PD+I) controller for robot manipulator [45].…”

Tuning ANFIS Using a Simplified Sparrow Search Algorithm

“…Duka applied ANFIS method to solve the inverse kinematics problem of robot manipulators [3]. Chaudhary, Panwar, Sukavanam, et al combined ANFIS and PID technique on the compliance control robot manipulators [4]. Hamouda, Babes, Kahla, et al applied ANFIS technique for MPPT of Solar PV System by using PSO Algorithm [5].…”