Incremental Polynomial Model-Controller Network: a self organising non-linear controller

Dear all,

Just to let you know of the http availability of a new technical
report entitled "Incremental Polynomial 
Model-Controller Network: a self organising non-linear controller" (it is a
compressed file. Please, gunzip the file to view or print it). 

http://www.mech.gla.ac.uk/~ericr/pub/csc9710.ps.gz

The report has been written by Eric Ronco and Peter J. Gawthrop. The
keywords are: Neural Networks, Control, Modelling, Self-Organisation.

Abstract:
The aim of this study is to present the "Incremental Polynomial
  Model-Controller Network" (IPMCN). This network is composed of
  controllers each one attached to a model used for its indirect
  design. At each instant the controller connected to the model
  performing the best is selected. An automatic network construction
  algorithm is discribed in this study. It makes the IPMCN a
  self-organising non-linear controller. However the emphasis is on
  the polynomial controllers that are the building blocks of the
  IPMCN.  From an analysis of the properties of polynomial functions
  for system modelling it is shown that multiple low order odd
  polynomials are very suitable to model non-linear systems. A closed
  loop reference model method to design a controller from a odd
  polynomial model is then described. The properties of the IPMCN are
  illustrated according to a second order system having both system
  states $y$ and $\dot{y}$ involving non-linear behaviour. It shows
  that as a component of a network or alone, a low order odd
  polynomial controller performs much better than a linear adaptive
  controller. Moreover, the number of controllers is significantly
  reduced with the increase of the polynomial order of the controllers
  and an improvement of the control performance is proportional to the
  decrease of the number of controllers. In addition,
  the clustering free approach, applied for the selection of the
  controllers, makes the IPMCN insensitive to the number of quantities
  involving non-linearity in the system. The use of local controllers
  capable of handling systems with complex dynamics will make this
  scheme one of the most effective approaches for the control of
  non-linear systems.



Regards,

Eric Ronco
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|  Eric Ronco                                                               |
|  Dt of Mechanical Engineering     E.mail : ericr at mech.gla.ac.uk           |
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|  Glasgow University               Tel : (44) (0)141 330 4370              |
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|  Scotland, UK                                                             |
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