Incremental Linear Controllers Network

نویسندگان

  • Eric Ronco
  • Peter J. Gawthrop
چکیده

The aim of this study is to introduce the Incremental Linear Controllers Network (ILCN). This algorithm consists of a linear controllers network (LCN) and a progressive control design algorithm (PCD). The LCN is a network of linear controllers each one being valid for a diierent operating region of the system. Such a control system can be used for the control of a (possibly discontinuous non linear system, it is not aaected by the \stability-plasticity dilemma" and yet can have a very clear architecture since it is composed of linear controllers. The PCD aims to resolve the clustering problem that faces any such multi-controller method. The PCD enables a very eecient construction of the network as well as an accurate determination of the region of validity of each controller. These features make the ILCN an eecient algorithm for the control of non linear systems using multiple linear controllers. We illustrate the behaviour of that algorithm according to the control of rst order non linear systems.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Incremental Model Reference Adaptive Polynomial Controllers Network

The Incremental Model Reference Adaptive Polynomial Controllers Network (IMRAPCN) is a self-organising non linear controller. This algorithm consists of a Polynomial Controllers Network (PCN) and an Incremental Network Construction (INC). The PCN is a network of polynomial controllers each one being valid for a diierent operating region of the system. The use of polynomial controllers reduces s...

متن کامل

Incremental Model Reference Adaptive

In this paper we are describing and illustrating the Incremental Model Reference Adaptive Polynomial Controllers Network (IMRAPCN). This algorithm is a polynomial version of the conventional linear controllers network. Two important properties of that system are: (1) its behaviour is clearly understandable because each polynomial controller can be interpreted in linear terms and (2) it is capab...

متن کامل

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

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...

متن کامل

Adaptive Predictive Controllers Using a Growing and Pruning RBF Neural Network

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

متن کامل

Neural network-based quality controllers for manufacturing systems

This paper demonstrates that neural networks can be used e€ ectively for quality control of non-linear static time-variant processes where the process physics and mechanistic models are not well understood. The emphasis of the paper is on models for both identi® cation and real-time process parameter design of manufacturing systems. Both multi-layer feed-forward perceptron networks and radial b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007