Fuzzy logic gain scheduling for non-linear servo tracking

Mieczysław Brdyś; Jonathan Littler

International Journal of Applied Mathematics and Computer Science (2002)

  • Volume: 12, Issue: 2, page 209-219
  • ISSN: 1641-876X

Abstract

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This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto the rate loop controller parameters. Consideration is given to the use of a derivative signal as a secondary input to the fuzzy inference system. Results are presented which demonstrate that this method of controlling the servo system gives a dramatic improvement over the traditional linear control methodology for low velocity tracking performance. A linear PID controller is used in the outer loop and its design is also given some consideration.

How to cite

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Brdyś, Mieczysław, and Littler, Jonathan. "Fuzzy logic gain scheduling for non-linear servo tracking." International Journal of Applied Mathematics and Computer Science 12.2 (2002): 209-219. <http://eudml.org/doc/207581>.

@article{Brdyś2002,
abstract = {This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto the rate loop controller parameters. Consideration is given to the use of a derivative signal as a secondary input to the fuzzy inference system. Results are presented which demonstrate that this method of controlling the servo system gives a dramatic improvement over the traditional linear control methodology for low velocity tracking performance. A linear PID controller is used in the outer loop and its design is also given some consideration.},
author = {Brdyś, Mieczysław, Littler, Jonathan},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {servo control; gain scheduling; stiction friction; tracking; hard non-linearities; fuzzy logic},
language = {eng},
number = {2},
pages = {209-219},
title = {Fuzzy logic gain scheduling for non-linear servo tracking},
url = {http://eudml.org/doc/207581},
volume = {12},
year = {2002},
}

TY - JOUR
AU - Brdyś, Mieczysław
AU - Littler, Jonathan
TI - Fuzzy logic gain scheduling for non-linear servo tracking
JO - International Journal of Applied Mathematics and Computer Science
PY - 2002
VL - 12
IS - 2
SP - 209
EP - 219
AB - This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto the rate loop controller parameters. Consideration is given to the use of a derivative signal as a secondary input to the fuzzy inference system. Results are presented which demonstrate that this method of controlling the servo system gives a dramatic improvement over the traditional linear control methodology for low velocity tracking performance. A linear PID controller is used in the outer loop and its design is also given some consideration.
LA - eng
KW - servo control; gain scheduling; stiction friction; tracking; hard non-linearities; fuzzy logic
UR - http://eudml.org/doc/207581
ER -

References

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