A Track Fuzzy Control of Robot Manipulator with Elastic Links

Modelling and control of manipulators with flexible links working on land and underwater environments

Robotica ◽

10.1017/s0263574710000305 ◽

2010 ◽

Vol 29 (3) ◽

pp. 461-470 ◽

Cited By ~ 5

Author(s):

Levent Gümüşel ◽

Nurhan Gürsel Özmen

Keyword(s):

Fuzzy Control ◽

Control Method ◽

Robot Manipulator ◽

Control Methods ◽

Control Laws ◽

Linear Ordinary Differential Equations ◽

Intelligent Technique ◽

Wide Range ◽

Classical Control ◽

And Control

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.

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Independent joint adaptive fuzzy control of robot manipulator

Proceedings of the 5th Biannual World Automation Congress ◽

10.1109/wac.2002.1049508 ◽

2003 ◽

Cited By ~ 5

Author(s):

V.T. Kim

Keyword(s):

Fuzzy Control ◽

Robot Manipulator ◽

Adaptive Fuzzy Control ◽

Adaptive Fuzzy

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Multiple Fuzzy Control of a Robot Manipulator.

TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C ◽

10.1299/kikaic.59.158 ◽

1993 ◽

Vol 59 (557) ◽

pp. 158-164 ◽

Cited By ~ 2

Author(s):

Sangho Jin ◽

Keigo Watanabe ◽

Masatoshi Nakamura

Keyword(s):

Fuzzy Control ◽

Robot Manipulator

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Neuro-fuzzy control of a robot manipulator for a trajectory design

Proceedings 6th IEEE International Workshop on Robot and Human Communication. RO-MAN'97 SENDAI ◽

10.1109/roman.1997.646992 ◽

2002 ◽

Author(s):

Jeong Kwang Son ◽

Hong You Sik ◽

Park Chong Kug

Keyword(s):

Fuzzy Control ◽

Robot Manipulator ◽

Trajectory Design ◽

Neuro Fuzzy

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Adaptive neural fuzzy control for robot manipulator friction and disturbance compensator

2008 International Conference on Control, Automation and Systems ◽

10.1109/iccas.2008.4694289 ◽

2008 ◽

Author(s):

Vu Minh Hung ◽

Uhn Joo Na

Keyword(s):

Fuzzy Control ◽

Robot Manipulator ◽

Neural Fuzzy

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Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2010.p0551 ◽

2010 ◽

Vol 22 (4) ◽

pp. 551-560

Author(s):

Ahmed Foad Amer ◽

◽

Elsayed Abdelhameed Sallam ◽

Wael Mohammed Elawady ◽

Keyword(s):

Fuzzy Control ◽

Fuzzy Controller ◽

Robot Manipulator ◽

Industrial Robot ◽

External Perturbation ◽

Gravity Compensation ◽

Pd Control ◽

Control Laws ◽

Self Tuning ◽

Fuzzy Pd

Industrial robot control covers nonlinearity, uncertainty and external perturbation considered in control laws design. Proportional and Derivative (PD) with gravity compensation control is well-known control used in manipulators to ensure global asymptotic stability for fixed symmetrical positive definite gain matrices. To enhance PD with gravity compensation controller performance, in this paper, we propose hybrid fuzzy PD control precompensation with gravity compensation, consisting of a fuzzy logic-based precompensator followed by hybrid fuzzy PD with gravity compensation controller. Hybrid fuzzy control is done by a Supervisory Hierarchical Fuzzy Controller (SHFC) for tuning conventional controller Proportional and Derivative gains based on actual tracking location and velocity error. Hierarchical hybrid fuzzy control consists of an intelligent upper supervisory fuzzy controller and a lower direct conventional PD controller. Numerical simulations using the dynamic model of a three DOF planar rigid robot manipulator with uncertainty show the effectiveness of the approach in trajectory tracking problems. Our results show that the proposal controller has performance superior to a conventional controller.

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