An iterative learning control law for dynamical systems

Automatica

Volumn 27, Issue 4, 1991, Pages 729-732

  Sugie, Toshiharu ^a   Ono, Toshiro ^b  

^a KYOTO UNIVERSITY   (Japan)

^b Osaka Prefecture University   (Japan)

Author keywords

learning control; nonlinear control systems; recursive algorithms; Robust control; tracking systems

Indexed keywords

CONTROL SYSTEMS, MULTIVARIABLE; CONTROL SYSTEMS, NONLINEAR - ROBUSTNESS; DYNAMICS; MATHEMATICAL TECHNIQUES - TRANSFER FUNCTIONS;

ITERATIVE LEARNING CONTROL LAW; RECURSIVE ALGORITHMS; TRACKING SYSTEMS;

LEARNING SYSTEMS;

EID: 0026186894     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/0005-1098(91)90066-B     Document Type: Article

References (11)

1. Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems
2. Bettering operation of robotics by learning
3. Can mechanical robots learn by themselves?
4. Learning control theory for dynamical systems
5. The design of learning control system for multivariable systems
6. Applications of learning method for dynamical control of robot manipulators
7. Proposal of betterment process A learning control method for dynamical systems
8. Iterative control and its application to motion control of robot arm
9. Input-output structure of linear systems with application to the decoupling problem
10. On an iterative learning control law for dynamical systems
11. Analysis and design of an optimal learning control scheme for industrial robots: A discrete system approach