Nonlinear Fuzzy Model-base Technique to Compensate Highly Nonlinear Continuum Robot Manipulator

Abstract

Abstract-Refer to this research, a grad ient descent optimization methodology for position fu zzy -model based computed torque controller (GDFCTC) is proposed for highly nonlinear continuum robot man ipulator. The main problem o f the pure co mputed torque controller (CTC) was equivalent problem in uncertain systems. The simulat ion results exhib it that the CTC works well in certain system. To eliminate the continuum robot manipulator system's dynamic; Mamdani fu zzy inference system is design and applied to CTC. Th is methodology is based on applied fu zzy logic in equivalent nonlinear dynamic part to estimate unknown parameters. This relatively controller is mo re plausible to implement in an actual real-t ime when compared to other techniques of nonlinear controller methodology of continuum arms. Based on the gradient descent optimizat ion method, the PD-gain updating factor has been developed in certain and part ly uncertain continuum robots. The new techniques proposed and methodologies adopted in this paper supported by MATLAB/SIM ULINK results represent a significant contribution to the field of design an optimized nonlinear co mputed torque controller for continuum robots.

Design New Online Tuning Intelligent Chattering Free Fuzzy Compensator

“…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].…”

“…Automatic control has played an important role in advance science and engineering and its extreme importance in many industrial applications, i.e., aerospace, mechanical engineering and robotic systems. The first significant wo rk in automat ic control was James Watt"s centrifugal governor for the speed control in motor engine in eighteenth century [41][42][43][44][45][46][47][48]. 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.…”

“…Th is control problem is classified into two main groups. Firstly, transformation the desired motion ( ) to joint variable ( ) by inverse kinemat ics of robot manipulators [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50]. This control include simple PD control, PID control, inverse dynamic control, Lyapunov-based control, and passivity based control that explained them in the following section.…”

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.…”

Novel Intelligent-Based Gravity Control for Industrial Robot Arm

“…Fuzzy logic theory is used to estimate the system's dynamics. To estimate the continuum robot manipulator's dynamic of system, Mamdani fuzzy inference system is design and applied to inverse dynamic methodology [12][13][14][15].…”