Reference : Identification of Non-Linear Dynamic Systems using an Expert Approach
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Mechanical engineering
Engineering, computing & technology : Aerospace & aeronautics engineering
http://hdl.handle.net/2268/24635
Identification of Non-Linear Dynamic Systems using an Expert Approach
English
Vio, Gareth Arthur [University of Manchester > School of Mechanical Aerospace and Civil Engineering > > >]
Dimitriadis, Grigorios mailto [Université de Liège - ULiège > Département d'aérospatiale et mécanique > Interactions Fluide-Structure - Aérodynamique expérimentale >]
Cooper, Jonathan Edward [University of Manchester > School of Mechanical Aerospace and Civil Engineering > > >]
May-2006
Proceedings of the 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
AIAA
Paper AIAA 2006-2037
No
No
International
USA
47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
du 1 mai au 4 mai 2006
AIAA, ASME, ASCE, AHS, ASC
Newport, Rhode Island
USA
[en] Nonlinear system identification ; Expert System
[en] An Expert System approach for the identification of non-linear systems is presented.
The Expert System is an attempt to bring order into the non-linear system identification
process. The final objective is to deliver a parsimonious mathematical model of the dy-
namical system under investigation. It works by defining the key stages of the procedure
and iterating between them if necessary. It takes advantage of numerous methodologies to
accomplish the tasks in each of the stages and uses the results from many of them. The
Expert System applies the excitation forces appropriate to each method and analyses the
responses. Each stage ends with a set of recommendations that can be used to begin the
next stage.
The Expert System is applied to a simple non-linear dynamic system. It is shown
that the Expert System procedure can automatically detect, locate and quantify the non-
linearity using its array of techniques. Furthermore, it can choose a suitable model struc-
ture, select appropriate terms and estimate the model parameters using an extensive set
of rules. The resulting identified model is validated and shown to be an accurate represen-
tation of the experimental system.
Researchers ; Professionals
http://hdl.handle.net/2268/24635
http://pdf.aiaa.org/preview/CDReadyMSDM06_1172/PV2006_2037.pdf

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