DocumentCode :
2124567
Title :
Adaptive neuro-predictive control of robot manipulators in work space
Author :
Mazdarani, H. ; Farrokhi, M.
Author_Institution :
Dept. of Electr. Eng., Iran Univ. of Sci. & Tehcnology, Tehran, Iran
fYear :
2012
fDate :
27-30 Aug. 2012
Firstpage :
349
Lastpage :
354
Abstract :
This paper proposes an adaptive Nonlinear Model Predictive Controller (NMPC) for hybrid position/velocity control of robot manipulators. Robot dynamics have generally uncertainties, including parameters variations, unknown nonlinearities of the robot, payload variations, and torque disturbances form the environment. The cost function of the NMPC is defined in such a way that by adjusting its weighting parameters, the end-effector of the robot tracks a predefined geometry path in Cartesian space with a constant velocity. Moreover, in order to cope with uncertainties in the robot model neural networks with Levenberg-Marquardt training algorithm will be used to estimate adaptively the model of the robot. The closed-loop stability is demonstrated using Lyapunov theory. Simulation results of the proposed control method applied to a 3-DOF manipulator actuated by DC servomotors show satisfactory results for trajectory tracking in work space of the robot.
Keywords :
DC motors; Lyapunov methods; adaptive control; closed loop systems; control nonlinearities; end effectors; geometry; manipulator dynamics; neurocontrollers; nonlinear control systems; predictive control; servomotors; stability; torque control; trajectory control; uncertain systems; velocity control; 3-DOF manipulator; Cartesian space; DC servomotor; Levenberg-Marquardt training algorithm; Lyapunov theory; NMPC; adaptive neuro-predictive control; adaptive nonlinear model predictive controller; closed-loop stability; constant velocity; cost function; end-effector; geometry path; hybrid position/velocity control; neural network; parameter variation; payload variation; robot dynamics; robot manipulator; robot uncertainties; robot work space; torque disturbance; trajectory tracking; unknown nonlinearities; Cost function; Joints; Manipulator dynamics; Servomotors; Levenberg-Marquardt algorithm; Lyapunov stability; Model predictive control; Neural-network model; Robot manipulators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Methods and Models in Automation and Robotics (MMAR), 2012 17th International Conference on
Conference_Location :
Miedzyzdrojie
Print_ISBN :
978-1-4673-2121-1
Type :
conf
DOI :
10.1109/MMAR.2012.6347864
Filename :
6347864
Link To Document :
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