Abstract/Details

Iterative learning control for nonsmooth dynamical systems


2007 2007

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Abstract (summary)

Iterative learning control (ILC) is a control technique that improves the performance of dynamical systems working in a repetitive mode. ILC emulates the human capability of learning from practice. In the same way a tennis player improves the shots after practicing over and over, an iterative learning controller uses previous trial information to get better performance of a system with respect to some desired performance objective.

ILC has been applied to robots performing repetitive tasks, where it has proven to be effective in compensating nonlinear effects such as gravity, Coriolis, and centrifugal forces. ILC has also been used in many other applications, e.g., batch chemical processes, injection molding machines, power electronics, and aerospace, to mention a few. However, ILC for nonsmooth dynamical systems has not been extensively explored. There has been some applications and heuristic procedures but not an analytical study for those cases. Examples of nonsmooth dynamics can be found in mechanical systems with dry (Coulomb) friction, systems with intermittent contacts, e.g., in robot assembly and walking robots, switching controllers such as in gain scheduling control, systems with backlash, systems containing discontinuous actuators like relays and solenoid valves, system with hysteresis, and switchings in electronic circuits. They are also present in economics and biology.

In this thesis, we analyze the implementation of ILC to nonsmooth dynamical systems. Two approaches for the design of ILC update laws are considered. The first approach is based on the application of the passivity theory. Derivation of the convergence of proportional ILC algorithms for nonsmooth systems containing incremental sector bounded nonlinearities is presented for the first time. The second approach uses the optimal control theory. Optimal control based ILC algorithms for nonsmooth Lipschitz continuous dynamical systems are derived and a new ILC algorithm capable of generating piecewise-continuous inputs for nonsmooth dynamical systems containing discontinuities is developed. As application examples, these ILC algorithms are tested on mechanical systems with intermittent contacts and on mechanical systems with dry friction.

Indexing (details)


Subject
Electrical engineering
Classification
0544: Electrical engineering
Identifier / keyword
Applied sciences; Control systems; Iterative learning control; Optimal control; Passivity
Title
Iterative learning control for nonsmooth dynamical systems
Author
Quintanilla Escalante, Rafael
Number of pages
111
Publication year
2007
Degree date
2007
School code
0185
Source
DAI-B 69/02, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9780549449874
Advisor
Wen, John T.; Arcak, Murat
University/institution
Rensselaer Polytechnic Institute
University location
United States -- New York
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3299469
ProQuest document ID
304839767
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/304839767
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