Intelligent predictive control of a model helicopter's yaw angle

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

In this paper the concept of Control Inertia is introduced and based on this concept, unexpectedly inadequate control behaviour of High Control Inertia systems is explained. Fuzzy compensators are then suggested to improve the control behaviour. This work is in the area of non-model-based control. In order to indicate the merit of the proposed technique, a neuro-predictive (NP) control is designed and implemented on a highly non-linear system, a lab helicopter, in a constrained situation. It is observed that the behaviour of the closed loop system under the NP controller either displays considerable function (with a low value of a particular design parameter) or is very slow (with high values of the same design parameter). In total, the control behaviour is very poor in comparison to existing fuzzy controllers, whereas NP is used effectively in the control of some other systems. Considering the concept of Control Inertia, a Sugeno-type fuzzy compensator was added to the control loop to modify the control command. A newly designed neuro-predictive control with fuzzy compensator (NPFC) improves the performance of the closed loop system significantly by the reduction of both overshoot and settling time. Furthermore, it is shown that the disturbance rejection of the NPFC controlled system as well as it parameter robustness is satisfactory.

Original languageEnglish
Pages (from-to)667-679
Number of pages13
JournalAsian Journal of Control
Volume12
Issue number6
DOIs
Publication statusPublished - Nov 2010

Fingerprint

Helicopters
Closed loop systems
Controllers
Disturbance rejection
Nonlinear systems
Control systems

Keywords

  • Control inertia
  • Fuzzy
  • Model helicopter
  • Neuro-predictive control
  • Yaw angle

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Intelligent predictive control of a model helicopter's yaw angle. / Mohammadzaheri, Morteza; Chen, Lei.

In: Asian Journal of Control, Vol. 12, No. 6, 11.2010, p. 667-679.

Research output: Contribution to journalArticle

@article{031981cb77c74aafa42fdb7177d9f194,
title = "Intelligent predictive control of a model helicopter's yaw angle",
abstract = "In this paper the concept of Control Inertia is introduced and based on this concept, unexpectedly inadequate control behaviour of High Control Inertia systems is explained. Fuzzy compensators are then suggested to improve the control behaviour. This work is in the area of non-model-based control. In order to indicate the merit of the proposed technique, a neuro-predictive (NP) control is designed and implemented on a highly non-linear system, a lab helicopter, in a constrained situation. It is observed that the behaviour of the closed loop system under the NP controller either displays considerable function (with a low value of a particular design parameter) or is very slow (with high values of the same design parameter). In total, the control behaviour is very poor in comparison to existing fuzzy controllers, whereas NP is used effectively in the control of some other systems. Considering the concept of Control Inertia, a Sugeno-type fuzzy compensator was added to the control loop to modify the control command. A newly designed neuro-predictive control with fuzzy compensator (NPFC) improves the performance of the closed loop system significantly by the reduction of both overshoot and settling time. Furthermore, it is shown that the disturbance rejection of the NPFC controlled system as well as it parameter robustness is satisfactory.",
keywords = "Control inertia, Fuzzy, Model helicopter, Neuro-predictive control, Yaw angle",
author = "Morteza Mohammadzaheri and Lei Chen",
year = "2010",
month = "11",
doi = "10.1002/asjc.243",
language = "English",
volume = "12",
pages = "667--679",
journal = "Asian Journal of Control",
issn = "1561-8625",
publisher = "National Taiwan University (IEEB)",
number = "6",

}

TY - JOUR

T1 - Intelligent predictive control of a model helicopter's yaw angle

AU - Mohammadzaheri, Morteza

AU - Chen, Lei

PY - 2010/11

Y1 - 2010/11

N2 - In this paper the concept of Control Inertia is introduced and based on this concept, unexpectedly inadequate control behaviour of High Control Inertia systems is explained. Fuzzy compensators are then suggested to improve the control behaviour. This work is in the area of non-model-based control. In order to indicate the merit of the proposed technique, a neuro-predictive (NP) control is designed and implemented on a highly non-linear system, a lab helicopter, in a constrained situation. It is observed that the behaviour of the closed loop system under the NP controller either displays considerable function (with a low value of a particular design parameter) or is very slow (with high values of the same design parameter). In total, the control behaviour is very poor in comparison to existing fuzzy controllers, whereas NP is used effectively in the control of some other systems. Considering the concept of Control Inertia, a Sugeno-type fuzzy compensator was added to the control loop to modify the control command. A newly designed neuro-predictive control with fuzzy compensator (NPFC) improves the performance of the closed loop system significantly by the reduction of both overshoot and settling time. Furthermore, it is shown that the disturbance rejection of the NPFC controlled system as well as it parameter robustness is satisfactory.

AB - In this paper the concept of Control Inertia is introduced and based on this concept, unexpectedly inadequate control behaviour of High Control Inertia systems is explained. Fuzzy compensators are then suggested to improve the control behaviour. This work is in the area of non-model-based control. In order to indicate the merit of the proposed technique, a neuro-predictive (NP) control is designed and implemented on a highly non-linear system, a lab helicopter, in a constrained situation. It is observed that the behaviour of the closed loop system under the NP controller either displays considerable function (with a low value of a particular design parameter) or is very slow (with high values of the same design parameter). In total, the control behaviour is very poor in comparison to existing fuzzy controllers, whereas NP is used effectively in the control of some other systems. Considering the concept of Control Inertia, a Sugeno-type fuzzy compensator was added to the control loop to modify the control command. A newly designed neuro-predictive control with fuzzy compensator (NPFC) improves the performance of the closed loop system significantly by the reduction of both overshoot and settling time. Furthermore, it is shown that the disturbance rejection of the NPFC controlled system as well as it parameter robustness is satisfactory.

KW - Control inertia

KW - Fuzzy

KW - Model helicopter

KW - Neuro-predictive control

KW - Yaw angle

UR - http://www.scopus.com/inward/record.url?scp=79952475583&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952475583&partnerID=8YFLogxK

U2 - 10.1002/asjc.243

DO - 10.1002/asjc.243

M3 - Article

AN - SCOPUS:79952475583

VL - 12

SP - 667

EP - 679

JO - Asian Journal of Control

JF - Asian Journal of Control

SN - 1561-8625

IS - 6

ER -