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Intelligent predictive control of a model helicopter's yaw angle
Author(s) -
Mohammadzaheri Morteza,
Chen Lei
Publication year - 2010
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.243
Subject(s) - control theory (sociology) , overshoot (microwave communication) , settling time , fuzzy control system , model predictive control , control system , fuzzy logic , control engineering , robustness (evolution) , inertia , engineering , computer science , control (management) , step response , artificial intelligence , biochemistry , chemistry , physics , electrical engineering , classical mechanics , gene
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. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society