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
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U2 - 10.1002/asjc.243
DO - 10.1002/asjc.243
M3 - Article
AN - SCOPUS:79952475583
SN - 1561-8625
VL - 12
SP - 667
EP - 679
JO - Asian Journal of Control
JF - Asian Journal of Control
IS - 6
ER -