K. Guglielmo et N. Sadegh, THEORY AND IMPLEMENTATION OF A REPETITIVE ROBOT CONTROLLER WITH CARTESIAN TRAJECTORY DESCRIPTION, Journal of dynamic systems, measurement, and control, 118(1), 1996, pp. 15-21
This paper presents a new repetitive learning controller for motion co
ntrol of mechanical manipulators undergoing periodic tasks defined in
Cartesian space. The controller does not require knowledge of the mani
pulator dynamic parameters beyond a simple geometric description. The
desired task will be defined in Cartesian coordinates, and no inverse
kinematics or inverse Jacobian will be calculated The asymptotic stabi
lity of this algorithm is proven using the Lyapunov approach, and the
nonlinear characteristics of the manipulator ave explicitly taken into
account. The results of implementation of this new repetitive learnin
g controller on an IBM 7545 robotic manipulator are presented Cartesia
n feedback was obtained from optical joint position encoders using for
ward kinematics, and velocity was estimated by simple numerical differ
entiation of the Cartesian position signal in software. The performanc
e of the algorithm was compared to that of a simple PD feedback system
, and a modified ''Computed Torque'' controller using inverse kinemati
cs on the Cartesian path. The learning algorithm outperformed both of
these controllers by a significant margin, exhibited convergence withi
n approximately three cycles, and did not require inverse kinematics t
o execute the Cartesian path.