Comparative Study between Two Important Nonlinear Methodologies for Continuum Robot Manipulator Control

Abstract

This research focuses on the basic concepts of continuum robot manipulator and control methodology. OCTARM Continuum robot manipulator is a 6 DOF serial robot manipulator. From the control point of view, robot manipulator divides into two main parts i.e. kinematics and dynamic parts. The dynamic parameters of this system are highly nonlinear. To control of this system nonlinear control methodology (computed torque controller and sliding mode controller) is introduced. Computed torque controller (CTC) is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required arm torques using the nonlinear feedback control law. When all dynamic and physical parameters are known computed torque controller works superbly; practically a large amount of systems have uncertainties and sliding mode controller reduce this kind of limitation. Sliding mode controller (SMC) is a significant nonlinear controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for robot manipulators, because this controller is a robust and stable. Comparative study between computed torque controller and sliding mode controller is introduced in this research.

Design New PID like Fuzzy CTC Controller: Applied to Spherical Motor

“…However, since joints coupling is neglected, control performance degrades as operating speed increases and a motor controlled in this way is only appropriate for relatively slow motion [44,46]. The fast motion requirement results in even higher dynamic coupling between the various spherical motor joints, which cannot be compensated for by a standard motor controller such as PID [50], and hence model-based control becomes the alternative.…”

“…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]. The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input.…”

“…Even though, this methodology is used in wide range areas but, pure computed torque method has an important drawbacks beside uncertain system and also in presence of external disturbance. Uncertainty in system can causes some problems about safety in industrial factory [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50].…”

Design Intelligent Model base Online Tuning Methodology for Nonlinear System

“…The remaining terms in the dynamic equations resulting from gravitational potential energies and spring energies are collected in the matrix . The coefficient matrices of the dynamic equations are given below, [58][59][60][61][62][63][64][65][66][67][68][69]. However the application area for fuzzy control is really wide, the basic form for all command types of controllers consists of;…”

“…The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input. This in turn would further inspire multi-uncertainties testing for continuum robot [58][59][60][61][62][63][64][65][66][67][68][69]. In project we can used fuzzy logic theory when a plant can be considered as a black box with outputs available for measurement and a possibility of changing inputs.…”