NDLI: Improvement tracking performances of adaptive model following control systems with unknown disturbances

Content Provider	IEEE Xplore Digital Library
Author	Maddi, A. Guessoum, A. Berkani, D.
Copyright Year	2015
Description	Author affiliation: Dept. of Electron., Univ. of Blida, Blida, Algeria (Maddi, A.; Guessoum, A.) \|\| Dept. of Electr. & Comput. Eng., Nat. Polytech. Sch. of Algiers, Algiers, Algeria (Berkani, D.)
Abstract	In this paper, an approach to Adaptive Model Following Control systems (AMFC) based on PID controller is proposed and analyzed for a class of Multi-Input Multi-Output (MIMO) linear time varying plant with unknown disturbances. This approach of design adaptive controller improved the performances of conventional AMFC schemes considerably, by incorporating an additional Proportional-Integral-Derivative (PID) action in the closed loop of hyper-stable AMFC systems. The controller parameters are designed under assumptions of unknown bounded disturbances, to a proper choice that satisfies the Popov stability criteria. Specifically, a control law is constructed of two essential components, the first one corresponds to AMFC systems without disturbances and the second one is responsible to reduce the effects of unknown load disturbances. Therefore, it's important to note that the method does not use any estimation algorithm and can guarantee an asymptotically stable state error for bounded disturbances. Finally, a numerical example is presented to show applicability and performances of the proposed approach.
Starting Page	1
Ending Page	6
File Size	319798
Page Count	6
File Format	PDF
e-ISBN	9781467366014
DOI	10.1109/ICMSAO.2015.7152232
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-27
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models Disturbance rejection Hyper-stability Model following Control systems Tracking error Numerical models Feedback control Mathematical model Adaptive control Load modeling
Content Type	Text
Resource Type	Article

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