Design Modified Fuzzy Hybrid Technique: Tuning By GDO

Abstract

The Proportional Integral Derivative (PID) Fuzzy hybrid (switching mode computed torque sliding mode) Controller is presented in this research. The popularity of PID FHC controllers can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID FHC controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. Biologically inspired evolutionary strategies have gained importance over other strategies because of their consistent performance over wide range of process models and their flexibility. This paper analyses the manual tuning techniques and compares the same with Gradient Descent tuning methods for tuning PID FHC controllers for flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator

Design New Online Tuning Intelligent Chattering Free Fuzzy Compensator

“…Calcu late several scale factors are common challenge in classical sliding mode controller and fu zzy logic controller, as a result it is used to adjust and tune coefficient. Research on adaptive fuzzy control is significantly growing, for instance, different adaptive fuzzy controllers have been reported in [40,[53][54][55]. This paper is organized as follows; second part focuses on the modeling dynamic fo rmulat ion based on Lagrange methodology, fuzzy logic methodology and sliding mode controller to have a robust control.…”

“…The applications of artificial intelligence such as neural networks and fuzzy logic in modelling and control are significantly growing especially in recent years. For instance, the applications of artificial intelligence, neural networks and fuzzy logic, on robot arm control have reported in [40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55].…”

“…This control methodology requires a greater algorithmic co mplexity and the inverse kinemat ics used in the feedback control loop. Direct measurement of operational space variables are very expensive that caused to limitation used of this controller in industrial robot manipulators [53][54][55]. One of the simp lest ways to analysis control of mult iple DOF robot man ipulators are analy zed each jo int separately such as SISO systems and design an independent joint controller for each jo int.…”

“…There are several methods for controlling a robot manipulator, which all of them follow t wo co mmon goals, namely, hardware/software imp lementation and acceptable performance. Ho wever, the mechanical design of robot man ipulator is very important to select the best controller but in general two types schemes can be presented, namely, a joint space control schemes and an operation space control schemes [49][50][51][52][53][54][55]. Joint space and operational space control are closed loop controllers which they have been used to provide robustness and rejection of disturbance effect.…”

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

“…At present, in some applications robot arms are used in unknown and unstructured environment, therefore strong mathematical tools used in new control methodologies to design nonlinear robust controller with an acceptable safety performance (e.g., minimum error, good trajectory, disturbance rejection). According to the control theory, Although the fuzzy-logic control is not a new technique, its application in this current research is considered to be novel since it aimed for an automated dynamic-less response rather than for the traditional objective of uncertainties compensation [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57]. The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input.…”