ITERATIVE LEARNING FOR TRAJECTORY CONTROL Conference Paper

abstract

• Learning control is an iterative approach to the problem of improving transient behavior for processes that are repetitive in nature. A complete analysis of the learning control problem is given for the case of linear, time-invariant plants and controllers. The analysis offers insights into the nature of the solution of learning control schemes. First an approach based on parameter estimation is given. Then it is shown that for finite-horizon problems it is possible to design a learning control algorithm which converges in one step. A brief simulation example is presented to illustrate the effectiveness of iterative learning for controlling the trajectory of a nonlinear robot manipulator.

name of conference

• Proceedings of the 28th IEEE Conference on Decision and Control

authors

• Bhattacharyya, S

published proceedings

• PROCEEDINGS OF THE 28TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-3

author list (cited authors)

• MOORE, K. L., DAHLEH, M., & BHATTACHARYYA, S. P.

citation count

• 20

complete list of authors

• MOORE, KL||DAHLEH, M||BHATTACHARYYA, SP

publication date

• January 1989

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Conference on Decision and Control  Journal

keywords

• 40 Engineering
• 4007 Control Engineering, Mechatronics And Robotics
• 4010 Engineering Practice And Education
• 49 Mathematical Sciences
• 4901 Applied Mathematics

Digital Object Identifier (DOI)

• 10.1109/CDC.1989.70243

start page

• 860

end page

• 865

volume

• 1

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Fcdc.1989.70243