Title :
Real-time decentralized neural block controller for a robot manipulator
Author :
Hernandez, R. Garcia ; Sanchez, E.N. ; Santibaez, V. ; Llama, M.A. ; Corrochano, E. Bayro
Author_Institution :
Fac. de Ing., Univ. Autonoma del Carmen, Campeche, Mexico
Abstract :
This paper presents a discrete-time decentralized control scheme for identification and trajectory tracking of a two degrees of freedom (DOF) robot manipulator. A recurrent high order neural network (RHONN) structure is used to identify the plant model and based on this model, a discrete-time control law is derived, which combines discrete-time block control and sliding modes techniques. The neural network learning is performed online by Kalman filtering. A controller is designed for each joint, using only local angular position and velocity measurements. These simple local joint controllers allow trajectory tracking with reduced computations. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.
Keywords :
Kalman filters; decentralised control; discrete time systems; learning (artificial intelligence); manipulators; neurocontrollers; position control; real-time systems; recurrent neural nets; variable structure systems; Kalman filtering; discrete-time decentralized control scheme; local angular position; local joint controller; neural network learning; real-time decentralized neural block controller; recurrent high order neural network; sliding modes technique; trajectory tracking; two-DOF robot manipulator; velocity measurement; Angular velocity control; Distributed control; Filtering; Kalman filters; Manipulators; Neural networks; Recurrent neural networks; Robot control; Sliding mode control; Trajectory;
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
DOI :
10.1109/IROS.2009.5354338
