Stochastic P-type/D-type iterative learning control algorithms

By Samer Said Saab Jr.. 2003

92 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Surgery

View Paper: https://www.semanticscholar.org/paper/99e97c6abfaf4098ac0569a5719a4422965b2dbe

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. YangQuan Chen
2. Andrew G. Alleyne
3. Marina Tharayil
4. Douglas A. Bristow
5. Hyo-Sung Ahn
6. Kevin L. Moore
7. Samer Said Saab Jr.
8. Ivo Petrás

Citations in the corpus

• Iterative Learning Control: Brief Survey and Categorization (2007, background): “disturbance rejection with feedback control [83]; disturbance rejection with iteration-varying filter [297]; nonlinear stochastic systems with unknown dynamics and unknown noise statistics [49]; stochastic ILC [48], [362]–[365] and with error prediction [15]; measurement noise [287], [296];”
• A survey of iterative learning control (2006, background): “The P-, D-, and PD-type learning functions are arguably the most widely used types of learning functions, particularly for nonlinear systems [5], [12], [39], [81], [83], [86]–[92].”
• A stochastic iterative learning control algorithm with application to an induction motor (2004, background): “The major system restriction for convergence, associated with Saab (2001, 2002, 2003), was that the system must possess a relative degree one.”