论文信息 - Iterative learning control synthesis based on 2-D system theory

Iterative learning control synthesis based on 2-D system theory

An algorithm is presented for iterative learning of the control input for a linear discrete-time multivariable system. Necessary and sufficient conditions are stated for convergence of the proposed algorithm. The algorithm synthesis and analysis are based on two-dimensional (2-D) system theory. A numerical example is given. >

J. Kurek | M. Zaremba

[1] R. Roesser. A discrete state-space model for linear image processing , 1975 .

[2] John J. Craig,et al. Adaptive control of manipulators through repeated trials , 1984 .

[3] J. E. Kurek,et al. Stabilities of 2-D Linear Discrete-Time Systems , 1984 .

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

[5] S. Arimoto,et al. Learning control theory for dynamical systems , 1985, 1985 24th IEEE Conference on Decision and Control.

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

[7] Jürgen Ackermann,et al. Sampled-Data Control Systems , 1985 .

[8] Katsuhisa Furuta,et al. Iterative generation of optimal input of a manipulator , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[9] Luca Maria Gambardella,et al. On the iterative learning control theory for robotic manipulators , 1988, IEEE J. Robotics Autom..

[10] Il Hong Suh,et al. An iterative learning control method with application to robot manipulators , 1988, IEEE J. Robotics Autom..

[11] R. Carroll,et al. Two-dimensional model and algorithm analysis for a class of iterative learning control systems , 1990 .

[12] Mo Jamshidi,et al. Learning control system analysis and design based on 2-D system theory , 1990, J. Intell. Robotic Syst..