Improving perfomance in single-link flexible manipulator using hybrid learning control

An iterative learning control method for a single-link flexible manipulator is proposed to achieve precise tracking control and end-point vibration suppression of the system. The learning is done in a feedback configuration with hybrid control and the learning law updates the feedforward input from the error of the previous trial. The dynamic model of the flexible manipulator is derived using the finite element method. Initially, a collocated proportional-derivative (pd) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. The controller is then extended to incorporate a non-collocated proportional-integral-derivative (pid) controller and a feedforward controller based on input shaping techniques for control of vibration flexible motion) of the system. Simulation results of the response of the manipulator with the controllers are presented in the time and frequency domains. The pe$ormance of the hybrid iterative learning control scheme is assessed in terms of input tracking and level of vibration reduction in comparison to a conventionally designed collocated pd and non-collocated pid control schemes.

[1]  S Arimoto,et al.  Convergence, stability and robustness of learning control schemes for robot manipulators , 1986 .

[2]  F. Miyazaki,et al.  Applications of learning method for dynamic control of robot manipulators , 1985, 1985 24th IEEE Conference on Decision and Control.

[3]  M. Osman Tokhi,et al.  Dynamic characterisation of a flexible manipulator system , 2001, Robotica.

[4]  Giovanni Ulivi,et al.  Disturbance rejection of iterative learning control applied to trajectory tracking for for a flexible manipulator , 1995 .

[5]  Z Mohamed,et al.  Vibration control of a single-link flexible manipulator using command shaping techniques , 2002 .

[6]  Kevin Warwick,et al.  Control systems : an introduction , 1989 .

[7]  Svante Gunnarsson,et al.  A Short Introduction to Iterative Learning Control , 1997 .

[8]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[9]  Roberto Horowitz,et al.  Learning Control of Robot Manipulators , 1993 .

[10]  Jian-Shiang Chen,et al.  Experiments on the payload-adaptation of a flexible one-link manipulation with unknown payload , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[11]  S. Shankar Sastry,et al.  Adaptive Control of Mechanical Manipulators , 1987, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[12]  E. Rogers,et al.  Iterative learning control for discrete-time systems with exponential rate of convergence , 1996 .

[13]  Musa Mailah.  Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm , 2000 .

[14]  John J. Craig,et al.  Hybrid Position/Force Control of Robot Manipulators , 1982 .

[15]  W. Gevarter.  Basic relations for control of flexible vehicles , 1969 .