Robust neural control for robotic manipulators
نویسندگان
چکیده
A robust neural control is designed for nonlinear dynamic systems. The objective of this work is to control the motion of the nonlinear system without any knowledge of its dynamics. This method of control requires only the measurement of the system state and its inputs. A Lyapunov function is proposed to ensure the stability of the nonlinear system equipped with the robust neural control. The online neural network’s learning algorithm is concluded. A case study of a three dimensional rigid-link robotic manipulator is developed. Simulation results of the robot manipulator demonstrate the efficiency of the proposed robust neural control.
منابع مشابه
Saturated Neural Adaptive Robust Output Feedback Control of Robot Manipulators:An Experimental Comparative Study
In this study, an observer-based tracking controller is proposed and evaluatedexperimentally to solve the trajectory tracking problem of robotic manipulators with the torque saturationin the presence of model uncertainties and external disturbances. In comparison with the state-of-the-artobserver-based controllers in the literature, this paper introduces a saturated observer-based controllerbas...
متن کاملOptimal discrete-time control of robot manipulators in repetitive tasks
Optimal discrete-time control of linear systems has been presented already. There are some difficulties to design an optimal discrete-time control of robot manipulator since the robot manipulator is highly nonlinear and uncertain. This paper presents a novel robust optimal discrete-time control of electrically driven robot manipulators for performing repetitive tasks. The robot performs repetit...
متن کاملAn Adaptive-Robust Control Approach for Trajectory Tracking of two 5 DOF Cooperating Robot Manipulators Moving a Rigid Payload
In this paper, a dual system consisting of two 5 DOF (RRRRR) robot manipulators is considered as a cooperative robotic system used to manipulate a rigid payload on a desired trajectory between two desired initial and end positions/orientations. The forward and inverse kinematic problems are first solved for the dual arm system. Then, dynamics of the system and the relations between forces/momen...
متن کاملGravity-Compensated Robust Control for Micro-Macro Space Manipulators During a Rest to Rest Maneuver
Many space applications require robotic manipulators which have large workspace and are capable of precise motion. Micro-macro manipulators are considered as the best solution to this demand. Such systems consist of a long flexible arm and a short rigid arm. Kinematic redundancy and presence of unactuated flexible degrees of freedom, makes it difficult to control micro-macro manipulators. This ...
متن کاملAdaptive RBF network control for robot manipulators
TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...
متن کاملDynamic modeling and control of a 4 DOF robotic finger using adaptive-robust and adaptive-neural controllers
In this research, first, kinematic and dynamic equations of a 4-DOF 3-link robotic finger are derived using Denavit-Hartenberg convention and Lagrange’s formulation. To model the muscles, several springs and dampers are placed between the finger links. Then, two advanced controllers, namely adaptive-robust and adaptive-neural, which can control the robotic finger in presence of parametric uncer...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Automatica
دوره 38 شماره
صفحات -
تاریخ انتشار 2002