Title :
Robust observer backstepping neural network control of flexible-joint manipulator
Author :
Chatlatanagulchai, Withit ; Nho, Hyuk Chul ; Meckl, Peter H.
Author_Institution :
Sch. of Mech. Eng., Purdue Univ., West Lafayette, IN, USA
fDate :
June 30 2004-July 2 2004
Abstract :
An output-feedback controller design for flexible-joint manipulators is presented. The proposed controller design consists of a nonlinear Luenberger-type observer, multilayer neural network plant identifier, and controller based on a backstepping framework and variable structure controller. Only link angular positions are measured as outputs. The controller achieves good performance despite the presence of additive external disturbances, unmodeled dynamics, actuator nonlinearities, i.e., deadzone and backlash, and payload changes. Simulation of a two-link flexible-joint manipulator is also included.
Keywords :
control nonlinearities; control system synthesis; feedback; flexible manipulators; manipulator dynamics; multilayer perceptrons; neurocontrollers; nonlinear control systems; observers; robust control; variable structure systems; actuator nonlinearities; backlash; backstepping neural network control; deadzone; multilayer neural network plant identifier; nonlinear Luenberger type observer; output feedback controller design; robust control; two link flexible joint manipulator; unmodeled dynamics; variable structure controller;
Conference_Titel :
American Control Conference, 2004. Proceedings of the 2004
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-8335-4