Design High Efficiency Intelligent Robust Backstepping Controller

Abstract

The increasing demand for multi-degree-offreedom (DOF) continuum robot in presence of highly nonlinear dynamic parameters in a number of industries has motivated a flurry of research in the development of soft computing nonlinear methodology. This research contributes to the ongoing research effort by exploring alternate methods for controlling the continuum robot manipulator. This research addresses two basic issues related to the control of a continuum robots; (1) a more accurate representation of the dynamic model of an existing prototype, and (2) the design of a robust feedback controller. The robust back stepping controller proposed in this research is used to further demonstrate the appealing features exhibited by the continuum robot. Robust feedback controller is used to position control of continuum robot in presence of uncertainties. Using Lyapunov type stability arguments, a robust back stepping controller is designed to achieve this objective. The controller developed in this research is designed into two steps. Firstly, a robust stabilizing torque is designed for the nominal continuum robot dynamics derived using the constrained Lagrangian formulation. Next, the fuzzy logic methodology applied to it to solution uncertainty problem. The fuzzy model free problem is formulated to minimize the nonlinear formulation of continuum robot. The eventual stability of the controller depends on the torque generating capabilities of the continuum robots.

Design Intelligent Robust Model-base Sliding Guidance Controller for Spherical Motor

“…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 [55][56][57][58][59][60][61][62][63][64][65][66]. In project we can use fuzzy logic theory when a plant can be considered as a black box with outputs available for measurement and a possibility of changing inputs.…”

Design Intelligent Robust Partly Linear Term SMC for Robot Manipulator Systems

“…This theory was first proposed in the early 1950 by Emelyanov and several co-workers and has been extensively developed since then with the invention o f high speed control devices . The main reason to opt for this controller is its acceptable control performance in wide range and solves two most important challenging topics in control which names, stability and robustness [41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59]. Sliding mode controller is d ivided into two main sub controllers: d iscontinues controller ( ) and equivalent controller( ).…”

“…Conversely in this theory good trajectory fo llo wing is based on fast switching, fast switching is caused to have system instability and chattering phenomenon. Fine tuning the sliding surface slope is based on nonlinear equivalent part [50][51][52][53][54][55][56][57][58][59]. However, this controller is used in many applicat ions but, pure sliding mode controller has two most important challenges: chattering phenomenon and nonlinear equivalent dynamic formu lation in uncertain parameters [55][56][57][58][59].…”

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.…”